Methods, kits and devices for identifying biomarkers of treatment response and use thereof to predict treatment efficacy

ABSTRACT

The present invention features methods, kits, and devices for predicting the sensitivity of a patient to a compound or medical treatment. The invention also features methods for identifying gene biomarkers whose expression correlates to treatment sensitivity or resistance within a patient population or subpopulation.

FIELD OF THE INVENTION

The invention features methods, kits, and devices for identifyingbiomarkers of patient sensitivity to medical treatments, e.g.,sensitivity to chemotherapeutic agents, and predicting treatmentefficacy using the biomarkers.

BACKGROUND OF THE INVENTION

DNA microarrays have been used to measure gene expression in tumorsamples from patients and to facilitate diagnosis. Gene expression canreveal the presence of cancer in a patient, its type, stage, and origin,and whether genetic mutations are involved. Gene expression may evenhave a role in predicting the efficacy of chemotherapy. Over recentdecades, the National Cancer Institute (NCI) has tested compounds,including chemotherapy agents, for their effect in limiting the growthof 60 human cancer cell lines. The NCI has also measured gene expressionin these 60 cancer cell lines using DNA microarrays. Various studieshave explored the relationship between gene expression and compoundeffect using the NCI datasets. Critical time is often lost due to atrial and error approach to finding an effective chemotherapy forpatients with cancer. In addition, cancer cells often develop resistanceto a previously effective therapy. In such situations, patient outcomecould be greatly improved by early detection of such resistance.

There remains a need for proven methods and devices that predict thesensitivity or resistance of cancer patients to a medical treatment.

SUMMARY OF THE INVENTION

The invention features methods, kits, and devices for determining thesensitivity or resistance of a patient, e.g., a cancer patient, to atreatment, e.g., treatment with a compound, such as a chemotherapeuticagent, or radiation. In particular, the methods, kits, and devices canbe used to determine the sensitivity or resistance of a cancer patientto any medical treatment, including, e.g., treatment with a compound,drug, or radiation. The methods, kits, and devices of the invention havebeen used to accurately determine treatment efficacy in cancer patients(e.g., patients with lung, lymphoma, and brain cancer) and can be usedto determine treatment efficacy in patients diagnosed with any cancer.

Methods, kits, and devices for detecting the level of expression ofbiomarkers (e.g., genes and microRNAs) that indicate sensitivity orresistance to radiation therapy or the chemotherapy agents Vincristine,Cisplatin, Azaguanine, Etoposide, Adriamycin, Aclarubicin, Mitoxantrone,Mitomycin, Paclitaxel, Gemcitabine, Taxotere, Dexamethasone, Ara-C,Methylprednisolone, Methotrexate, Bleomycin, Methyl-GAG, Carboplatin,5-FU (5-Fluorouracil), Rituximab, PXD101, (a histone deacetylase (HDAC)inhibitor), 5-Aza-2′-deoxycytidine (Decitabine), Melphalan, IL4-PE38fusion protein, IL13-PE38QQR fusion protein (cintredekin besudotox),Valproic acid (VPA), All-trans retinoic acid (ATRA), Cytoxan, Topotecan(Hycamtin), Suberoylanilide hydroxamic acid (SAHA, vorinostat, Zolinza),Depsipeptide (FR901229), Bortezomib, Leukeran, Fludarabine, Vinblastine,Busulfan, Dacarbazine, Oxaliplatin, Hydroxyurea, Tegafur, Daunorubicin,Bleomycin, Estramustine, Chlorambucil, Mechlorethamine, Streptozocin,Carmustine, Lomustine, Mercaptopurine, Teniposide, Dactinomycin,Tretinoin, Sunitinib, SPC2996, Ifosfamide, Tamoxifen, Floxuridine,Irinotecan, and Satraplatin are also provided. The methods, kits, anddevices can be used to predict the sensitivity or resistance of asubject (e.g., a cancer patient) diagnosed with a disease condition,e.g., cancer (e.g., cancers of the breast, prostate, lung and bronchus,colon and rectum, urinary bladder, skin, kidney, pancreas, oral cavityand pharynx, ovary, thyroid, parathyroid, stomach, brain, esophagus,liver and intrahepatic bile duct, cervix larynx, heart, testis, smalland large intestine, anus, anal canal and anorectum, vulva, gallbladder,pleura, bones and joints, hypopharynx, eye and orbit, nose, nasal cavityand middle ear, nasopharynx, ureter, peritoneum, omentum and mesentery,or gastrointestines, as well as any form of cancer including, e.g.,chronic myeloid leukemia, acute lymphocytic leukemia, non-Hodgkin'slymphoma, melanoma, carcinoma, basal cell carcinoma, malignantmesothelioma, neuroblastoma, multiple myeloma, leukemia, retinoblastoma,acute myeloid leukemia, chronic lymphocytic leukemia, Hodgkin'slymphoma, carcinoid tumors, acute tumor, or soft tissue sarcoma) to atreatment, e.g., treatment with a compound or drug, e.g., achemotherapeutic agent, or radiation.

In a first aspect, the invention features a method of determiningsensitivity of a cancer in a patient to a treatment for cancer bymeasuring the level of expression of at least one gene in a cell (e.g.,a cancer cell) of the patient, in which the gene is selected from thegroup consisting of ACTB, ACTN4, ADA, ADAM9, ADAMTS1, ADD1, AF1Q, AIF1,AKAP1, AKAP13, AKR1C1, AKT1, ALDH2, ALDOC, ALG5, ALMS1, ALOX15B, AMIGO2,AMPD2, AMPD3, ANAPC5, ANP32A, ANP32B, ANXA1, AP1G2, APOBEC3B, APRT,ARHE, ARHGAP15, ARHGAP25, ARHGDIB, ARHGEF6, ARL7, ASAH1, ASPH, ATF3,ATIC, ATP2A2, ATP2A3, ATP5D, ATP5G2, ATP6V1B2, BC008967, BCAT1, BCHE,BCL11B, BDNF, BHLHB2, BIN2, BLMH, BMI1, BNIP3, BRDT, BRRN1, BTN3A3,C11orf2, C14orf139, C15orf25, C18orf10, C1orf24, C1orf29, C1orf38,C1QR1, C22orf18, C6orf32, CACNA1G, CACNB3, CALM1, CALML4, CALU, CAP350,CASP2, CASP6, CASP7, CAST, CBLB, CCNA2, CCNB1IP1, CCND3, CCR7, CCR9,CD1A, CD1C, CD1D, CD1E, CD2, CD28, CD3D, CD3E, CD3G, CD3Z, CD44, CD47,CD59, CD6, CD63, CD8A, CD8B1, CD99, CDC10, CDCl₄B, CDH11, CDH2, CDKL5,CDKN2A, CDW52, CECR1, CENPB, CENTB1, CENTG2, CEP1, CG018, CHRNA3, CHS1,CIAPIN1, CKAP4, CKIP-1, CNP, COL4A1, COL5A2, COL6A1, CORO1C, CRABP1,CRK, CRY1, CSDA, CTBP1, CTSC, CTSL, CUGBP2, CUTC, CXCL1, CXCR4, CXorf9,CYFIP2, CYLD, CYR61, DATF1, DAZAP1, DBN1, DBT, DCTN1, DDX18, DDX5, DGKA,DIAPH1, DKC1, DKFZP434J154, DKFZP564C186, DKFZP564G2022, DKFZp564J157,DKFZP564K0822, DNAJC10, DNAJC7, DNAPTP6, DOCK10, DOCK2, DPAGT1, DPEP2,DPYSL3, DSIPI, DUSP1, DXS9879E, EEF1B2, EFNB2, EHD2, EIF5A, ELK3, ENO2,EPAS1, EPB41L4B, ERCC2, ERG, ERP70, EVER1, EVI2A, EVL, EXT1, EZH2, F2R,FABP5, FAD104, FAM46A, FAU, FCGR2A, FCGR2C, FER1L3, FHL1, FHOD1, FKBP1A,FKBP9, FLJ10350, FLJ10539, FLJ10774, FLJ12270, FLJ13373, FLJ20859,FLJ21159, FLJ22457, FLJ35036, FLJ46603, FLNC, FLOT1, FMNL1, FNBP1,FOLH1, FOXF2, FSCN1, FTL, FYB, FYN, GOS2, G6PD, GALIG, GALNT6, GATA2,GATA3, GFPT1, GIMAP5, GIT2, GJA1, GLRB, GLTSCR2, GLUL, GMDS, GNAQ, GNB2,GNB5, GOT2, GPR65, GPRASP1, GPSM3, GRP58, GSTM2, GTF3A, GTSE1, GZMA,GZMB, H1F0, H1FX, H2AFX, H3F3A, HA-1, HEXB, HIC, HIST1H4C, HK1, HLA-A,HLA-B, HLA-DRA, HMGA1, HMGN2, HMMR, HNRPA1, HNRPD, HNRPM, HOXA9,HRMT1L1, HSA9761, HSPA5, HSU79274, HTATSF1, ICAM1, ICAM2, IER3, IFI16,IFI44, IFITM2, IFITM3, IFRG28, IGFBP2, IGSF4, IL13RA2, IL21R, IL2RG,IL4R, IL6, IL6R, IL6ST, IL8, IMPDH2, INPP5D, INSIG1, IQGAP1, IQGAP2,IRS2, ITGA5, ITM2A, JARID2, JUNB, K-ALPHA-1, KHDRBS1, KIAA0355,KIAA0802, KIAA0877, KIAA0922, KIAA1078, KIAA1128, KIAA1393, KIFC1,LAIR1, LAMB1, LAMB3, LAT, LBR, LCK, LCP1, LCP2, LEF1, LEPRE1, LGALS1,LGALS9, LHFPL2, LNK, LOC54103, LOC55831, LOC81558, LOC94105, LONP, LOX,LOXL2, LPHN2, LPXN, LRMP, LRP12, LRRC5, LRRN3, LST1, LTB, LUM, LY9,LY96, MAGEB2, MAL, MAP1B, MAP1LC3B, MAP4K1, MAPK1, MARCKS, MAZ, MCAM,MCL1, MCM5, MCM7, MDH2, MDN1, MEF2C, MFNG, MGC17330, MGC21654, MGC2744,MGC4083, MGC8721, MGC8902, MGLL, MLPH, MPHOSPH6, MPP1, MPZL1, MRP63,MRPS2, MT1E, MT1K, MUF1, MVP, MYB, MYL9, MYO1B, NAP1L1, NAP1L2, NARF,NASP, NCOR2, NDN, NDUFAB1, NDUFS6, NFKBIA, NID2, NIPA2, NME4, NME7,NNMT, NOL5A, NOL8, NOMO2, NOTCH1, NPC1, NQO1, NR1D2, NUDC, NUP210,NUP88, NVL, NXF1, OBFC1, OCRL, OGT, OXA1L, P2RX5, P4HA1, PACAP, PAF53,PAFAH1B3, PALM2-AKAP2, PAX6, PCBP2, PCCB, PFDN5, PFN1, PFN2, PGAM1,PHEMX, PHLDA1, PIM2, PITPNC1, PLAC8, PLAGL1, PLAUR, PLCB1, PLEK2,PLEKHC1, PLOD2, PLSCR1, PNAS-4, PNMA2, POLR2F, PPAP2B, PRF1, PRG1,PRIM1, PRKCH, PRKCQ, PRKD2, PRNP, PRP19, PRPF8, PRSS23, PSCDBP, PSMB9,PSMC3, PSME2, PTGER4, PTGES2, PTOV1, PTP4A3, PTPN7, PTPNS1, PTRF, PURA,PWP1, PYGL, QKI, RAB3GAP, RAB7L1, RAB9P40, RAC2, RAFTLIN, RAG2, RAP1B,RASGRP2, RBPMS, RCN1, RFC3, RFC5, RGC32, RGS3, RHOH, RIMS3, RIOK3,RIPK2, RIS1, RNASE6, RNF144, RPL10, RPL10A, RPL12, RPL13A, RPL17, RPL18,RPL36A, RPLP0, RPLP2, RPS15, RPS19, RPS2, RPS4X, RPS4Y1, RRAS, RRAS2,RRBP1, RRM2, RUNX1, RUNX3, S100A4, SART3, SATB1, SCAP1, SCARB1, SCN3A,SEC31L2, SEC61G, SELL, SELPLG, SEMA4G, SEPT10, SEPT6, SERPINA1,SERPINB1, SERPINB6, SFRS5, SFRS6, SFRS7, SH2D1A, SH3GL3, SH3TC1, SHD1,SHMT2, SIAT1, SKB1, SKP2, SLA, SLC1A4, SLC20A1, SLC25A15, SLC25A5,SLC39A14, SLC39A6, SLC43A3, SLC4A2, SLC7A11, SLC7A6, SMAD3, SMOX, SNRPA,SNRPB, SOD2, SOX4, SP140, SPANXC, SPI1, SRF, SRM, SSA2, SSBP2, SSRP1,SSSCA1, STAG3, STAT1, STAT4, STAT5A, STC1, STC2, STOML2, T3JAM, TACC1,TACC3, TAF5, TAL1, TAP1, TARP, TBCA, TCF12, TCF4, TFDP2, TFPI, TIMM17A,TIMP1, TJP1, TK2, TM4SF1, TM4SF2, TM4SF8, TM6SF1, TMEM2, TMEM22, TMSB10,TMSNB, TNFAIP3, TNFAIP8, TNFRSF10B, TNFRSF1A, TNFRSF7, TNIK, TNPO1,TOB1, TOMM20, TOX, TPK1, TPM2, TRA@, TRA1, TRAM2, TRB@, TRD@, TRIM,TRIM14, TRIM22, TRIM28, TRIP13, TRPV2, TUBGCP3, TUSC3, TXN, TXNDC5,UBASH3A, UBE2A, UBE2L6, UBE2S, UCHL1, UCK2, UCP2, UFD1L, UGDH, ULK2,UMPS, UNG, USP34, USP4, VASP, VAV1, VLDLR, VWF, WASPIP, WBSCR20A,WBSCR20C, WHSC1, WNT5A, ZAP70, ZFP36L1, ZNF32, ZNF335, ZNF593, ZNFN1A1,and ZYX; in which change in the level of expression of the geneindicates the cell is sensitive or resistant to the treatment.

In an embodiment, the method further includes determining a patient'sresistance or sensitivity to radiation therapy or the chemotherapyagents Vincristine, Cisplatin, Adriamycin, Etoposide, Azaguanine,Aclarubicin, Mitoxantrone, Paclitaxel, Mitomycin, Gemcitabine, Taxotere,Dexamethasone, Methylprednisolone, Ara-C, Methotrexate, Bleomycin,Methyl-GAG, Rituximab, PXD101 (a histone deacetylase (HDAC) inhibitor),5-Aza-2′-deoxycytidine (Decitabine), Melphalan, IL4-PE38 fusion protein,IL13-PE38QQR fusion protein (cintredekin besudotox), Valproic acid(VPA), All-trans retinoic acid (ATRA), Cytoxan, Topotecan (Hycamtin),Suberoylanilide hydroxamic acid (SAHA, vorinostat, Zolinza),Depsipeptide (FR901229), Bortezomib, Leukeran, Fludarabine, Vinblastine,Busulfan, Dacarbazine, Oxaliplatin, Hydroxyurea, Tegafur, Daunorubicin,Bleomycin, Estramustine, Chlorambucil, Mechlorethamine, Streptozocin,Carmustine, Lomustine, Mercaptopurine, Teniposide, Dactinomycin,Tretinoin, Sunitinib, SPC2996, Ifosfamide, Tamoxifen, Floxuridine,frinotecan, and Satraplatin by measuring the level of expression of oneor more of the genes known to change (e.g., to increase or decrease) ina patient sensitive to treatment with these agents (e.g., a patient isdetermined to be sensitive, or likely to be sensitive, to the indicatedtreatment if the level of expression of one or more of the gene(s)increases or decreases relative to the level of expression of thegene(s) in a control sample (e.g., a cell or tissue) in which increasedor decreased expression of the gene(s) indicates sensitivity to thetreatment, and vice versa). Alternatively, a patient's resistance orsensitivity to radiation therapy or any of the chemotherapy agentslisted above can be determined by measuring the level of expression ofat least one microRNA in a cell (e.g., a cancer cell) known to change(e.g., the level of expression is increased or decreased) in a patientsensitive to a treatment with these agents, in which the microRNA isselected from the group consisting of ath-MIR180aNo2, Hcd102 left,Hcd111 left, Hcd115 left, Hcd120 left, Hcd142 right, Hcd145 left,Hcd148_HPR225 left, Hcd181 left, Hcd181 right, Hcd210_HPR205 right,Hcd213_HPR182 left, Hcd230 left, Hcd243 right, Hcd246 right, Hcd248right, Hcd249 right, Hcd250 left, Hcd255 left, Hcd257 left, Hcd257right, Hcd263 left, Hcd266 left, Hcd270 right, Hcd279 left, Hcd279right, Hcd28_HPR39left, Hcd28_HPR39right, Hcd282PO right, Hcd289 left,Hcd294 left, Hcd318 right, Hcd323 left, Hcd330 right, Hcd338 left,Hcd340 left, Hcd350 right, Hcd355_HPR190 left, Hcd361 right, Hcd366left, Hcd373 right, Hcd383 left, Hcd383 right, Hcd384 left, Hcd397 left,Hcd404 left, Hcd412 left, Hcd413 right, Hcd415 right, Hcd417 right,Hcd421 right, Hcd425 left, Hcd438right, Hcd434 right, Hcd438 left,Hcd440_HPR257 right, Hcd444 right, Hcd447 right, Hcd448 left, Hcd498right, Hcd503 left, Hcd511 right, Hcd512 left, Hcd514 right, Hcd517left, Hcd517 right, Hcd530 right, Hcd536_HPR104 right, Hcd542 left,Hcd544 left, Hcd547 left, Hcd559 right, Hcd562 right, Hcd569 right,Hcd570 right, Hcd578 right, Hcd581 right, Hcd586 left, Hcd586 right,Hcd587 right, Hcd605 left, Hcd605 left, Hcd605 right, Hcd608 right,Hcd627 left, Hcd631 left, Hcd631 right, Hcd634 left, Hcd642 right,Hcd649 right, Hcd654 left, Hcd658 right, Hcd669 right, Hcd674 left,Hcd678 right, Hcd683 left, Hcd684 right, Hcd689 right, Hcd690 right,Hcd691 right, Hcd693 right, Hcd697 right, Hcd704 left, Hcd704 left,Hcd712 right, Hcd716 right, Hcd731 left, Hcd738 left, Hcd739 right,Hcd739 right, Hcd749 right, Hcd753 left, Hcd754 left, Hcd755 left,Hcd760 left, Hcd763 right, Hcd768 left, Hcd768 right, Hcd770 left,Hcd773 left, Hcd777 left, Hcd778 right, Hcd781 left, Hcd781 right,Hcd782 left, Hcd783 left, Hcd788 left, Hcd794 right, Hcd796 left, Hcd799left, Hcd807 right, Hcd812 left, Hcd817 left, Hcd817 right, Hcd829right, Hcd852 right, Hcd861 right, Hcd863PO right, Hcd866 right, Hcd869left, Hcd873 left, Hcd886 right, Hcd889 right, Hcd891 right, Hcd892left, Hcd913 right, Hcd923 left, Hcd923 right, Hcd938 left, Hcd938right, Hcd939 right, Hcd946 left, Hcd948 right, Hcd960 left, Hcd965left, Hcd970 left, Hcd975 left, Hcd976 right, Hcd99 right, HPR100 right,HPR129 left, HPR154 left, HPR159 left, HPR163 left, HPR169 right, HPR172right, HPR181 left, HPR187 left, HPR199 right, HPR206 left, HPR213right, HPR214 right, HPR220 left, HPR220 right, HPR227 right, HPR232right, HPR233 right, HPR244 right, HPR262 left, HPR264 right, HPR266right, HPR271 right, HPR76 right, hsa_mir_(—)490_Hcd20 right, HSHELA01,HSTRNL, HUMTRAB, HUMTRF, HUMTRN, HUMTRS, HUMTRV1A, let-7f-2-prec2,mir-001b-1-prec1, mir-001b-2-prec, mir-007-1-prec, mir-007-2-precNo2,mir-010a-precNo1, mir-015b-precNo2, mir-016a-chr13, mir-016b-chr3,mir-0,7-precNo1, mir-0,7-precNo2, mir-018-prec, mir-019a-prec,mir-019b-1-prec, mir-019b-2-prec, mir-020-prec, mir-022-prec,mir-023a-prec, mir-023b-prec, mir-024-2-prec, mir-025-prec,mir-027b-prec, mir-029c-prec, mir-032-precNo2, mir-033b-prec,mir-033-prec, mir-034-precNo1, mir-034-precNo2,mir-092-prec-13=092-1No2, mir-092-prec-X=092-2, mir-093-prec-7.1=093-1,mir-095-prec-4,mir-096-prec-7No1, mir-096-prec-7No2, mir-098-prec-X,mir-099b-prec-19No1, mir-100-1/2-prec, mir-100No1, mir-101-prec-9,mir-102-prec-1, mir-103-2-prec, mir-103-prec-5=103-1, mir-106aNo1,mir-106-prec-X, mir-107No1, mir-107-prec-10, mir-122a-prec,mir-123-precNo1, mir-123-precNo2, mir-124a-1-prec1, mir-124a-2-prec,mir-124a-3-prec, mir-125b-1, mir-125b-2-precNo2, mir-127-prec,mir-128b-precNo1, mir-128b-precNo2, mir-133a-1, mir-135-2-prec,mir-136-precNo2, mir-138-1-prec, mir-140No2, mir-142-prec, mir-143-prec,mir-144-precNo2, mir-145-prec, mir-146bNo1, mir-146-prec, mir-147-prec,mir-148aNo1, mir-148-prec, mir-149-prec, mir-150-prec, mir-153-1-prec1,mir-154-prec1No1, mir-155-prec, mir-15aNo1, mir-16-1No1, mir-16-2No1,mir-181a-precNo1, mir-181b-1No1, mir-181b-2No1, mir-181b-precNo1,mir-181b-precNo2, mir-181c-precNo1, mir-181dNo1, mir-188-prec,mir-18bNo2, mir-191-prec, mir-192No2, mir-193bNo2, mir-194-2No1,mir-195-prec, mir-196-2-precNo2, mir-197-prec, mir-198-prec,mir-199a-1-prec, mir-199a-2-prec, mir-199b-precNo1, mir-200a-prec,mir-200bNo1, mir-200bNo2, mir-202*, mir-202-prec, mir-204-precNo2,mir-205-prec, mir-208-prec, mir-20bNo1, mir-2,2-precNo1,mir-2,2-precNo2, mir-2,3-precNo1, mir-2,4-prec, mir-2,5-precNo2,mir-2,6-precNo1, mir-219-2No1, mir-2,9-prec, mir-223-prec, mir-29b-1No1,mir-29b-2=102prec7.1=7.2, mir-321No1, mir-321No2, mir-324No1,mir-324No2, mir-328No1, mir-342No1, mir-361No1, mir-367No1, mir-370No1,mir-371No1, miR-373*No1, mir-375, mir-376aNo1, mir-379No1, mir-380-5p,mir-382, mir-384, mir-409-3p, mir-423No1, mir-424No2, mir-429No1,mir-429No2, mir-4323p, mir-4325p, mir-449No1, mir-450-1, mir-450-2No1,mir-483No1, mir-484, mir-487No1, mir-495No1, mir-499No2, mir-501No2,mir-503No1, mir-509No1, mir-514-1No2, mir-515-15p, mir-515-23p,mir-516-33p, mir-516-43p, mir-518e/526c, mir-519a-1/52, mir-519a-2No2,mir-519b, mir-519c/52, mir-520c/52, mir-526a-2No1, mir-526a-2No2, MPR103right, MPR121 left, MPR121 left, MPR130 left, MPR130 right, MPR133right, MPR141 left, MPR151 left, MPR156 left, MPR162 left, MPR174 left,MPR174 right, MPR185 right, MPR197 right, MPR203 left, MPR207 right,MPR215 left, MPR216 left, MPR224 left, MPR224 right, MPR228 left, MPR234right, MPR237 left, MPR243 left, MPR244 right, MPR249 left, MPR254right, MPR74 left, MPR88 right, and MPR95 left.

In an embodiment, the method includes determining the expression of twoof the listed genes or microRNAs, more preferably three, four, five,six, seven, eight, nine, or ten of the listed genes, and most preferablytwenty, thirty, forty, fifty, sixty, seventy, eighty, ninety, or onehundred or more of the listed genes. In another embodiment, the changein the level of gene or microRNA expression (e.g., an increase ordecrease) is determined relative to the level of gene or microRNAexpression in a cell or tissue known to be sensitive to the treatment,such that a similar level of gene or microRNA expression exhibited by acell or tissue of the patient indicates the patient is sensitive to thetreatment. In another embodiment, the change in the level of gene ormicroRNA expression (e.g., an increase or decrease) is determinedrelative to the level of gene or microRNA expression in a cell or tissueknown to be resistant to the treatment, such that a similar level ofgene or microRNA expression exhibited by a cell or tissue of the patientindicates the patient is resistant to the treatment.

In a second aspect, the invention features a method of determiningsensitivity of a cancer in a patient to a treatment for cancer bymeasuring the level of expression of at least one microRNA in a cell(e.g., a cancer cell) of the patient, in which the microRNA is selectedfrom the group set forth in the first aspect of the invention. In anembodiment, the method further includes determining a patient'sresistance or sensitivity to radiation therapy or any of thechemotherapy agents set forth in the first aspect of the invention bymeasuring the level of expression of one or more of the microRNAs knownto change (e.g., to increase or decrease) in a patient sensitive totreatment with these agents (e.g., a patient is determined to besensitive, or likely to be sensitive, to the indicated treatment if thelevel of expression of one or more of the microRNA(s) increases ordecreases relative to the level of expression of the microRNA(s) in acontrol sample (e.g., a cell or tissue) in which increased or decreasedexpression of the microRNA(s) indicates sensitivity to the treatment,and vice versa). In an embodiment, the method includes determining theexpression of two of the listed genes or microRNAs, more preferablythree, four, five, six, seven, eight, nine, or ten of the listed genes,and most preferably twenty, thirty, forty, fifty, sixty, seventy,eighty, ninety, or one hundred or more of the listed genes. In anotherembodiment, the change in the level of microRNA expression (e.g., anincrease or decrease) is determined relative to the level of microRNAexpression in a cell or tissue known to be sensitive to the treatment,such that a similar level of microRNA expression exhibited by a cell ortissue of the patient indicates the patient is sensitive to thetreatment. In another embodiment, the change in the level of microRNAexpression (e.g., an increase or decrease) is determined relative to thelevel of microRNA expression in a cell or tissue known to be resistantto the treatment, such that a similar level of microRNA expressionexhibited by a cell or tissue of the patient indicates the patient isresistant to the treatment.

In another embodiment, the invention features a method for determiningthe development of resistance by a patient (e.g., resistance of a cell,such as a cancer cell, in the patient) to a treatment to which thepatient was previously sensitive. The method includes measuring thelevel of expression of one or more of the microRNAs set forth in thefirst aspect of the invention, such that the level of expression of amicroRNA which is decreased in a cell or tissue known to be sensitive tothe treatment indicates that the patient is resistant to or has apropensity to become resistant to the treatment. Alternatively, adecrease in the expression level of a microRNA which is increased in acell or tissue known to be sensitive to the treatment indicates that thepatient is resistant to or has a propensity to become resistant to thetreatment.

In a third aspect, the invention features a kit that includes asingle-stranded nucleic acid molecule (e.g., one or a plurality thereof;e.g., a deoxyribonucleic acid molecule or a ribonucleic acid molecule)that is substantially complementary to (e.g., that has at least 80%,90%, 95% 97%, 99%, or 100% identical to the complement of) or that issubstantially identical to (e.g., that has at least 80%, 90%, 95% 97%,99%, or 100% identity to) at least 5 consecutive nucleotides (morepreferably at least 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70,75, 80, 85, 90, 95, 100, 150, 200, 250, 300, or more consecutivenucleotides; the nucleic acid can also be 5-20, 25, 5-50, 50-100, orover 100 consecutive nucleotides long) of at least one of the genes(e.g., at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80,90, 100, or more of the genes) set forth in the first aspect of theinvention, such that the single-stranded nucleic acid molecule issufficient for measuring the level of expression of the gene(s) byallowing specific hybridization between the single-stranded nucleic acidmolecule and a nucleic acid molecule encoded by the gene, or acomplement thereof. Alternatively, the kit includes one or moresingle-stranded nucleic acid molecules that are substantiallycomplementary to or substantially identical to at least 5 consecutivenucleotides of at least one of the microRNAs set forth in the firstaspect of the invention, such that the single-stranded nucleic acidmolecule is sufficient for measuring the level of expression of themicroRNA(s) by allowing specific hybridization between thesingle-stranded nucleic acid molecule and the microRNA, or a complementthereof. The kit further includes instructions for applying nucleic acidmolecules collected from a sample from a cancer patient (e.g., from acell of the patient), determining the level of expression of the gene(s)or microRNA(s) hybridized to the single-stranded nucleic acid, anddetermining the patient's sensitivity to a treatment for cancer when useof the kit indicates that the level of expression of the gene(s) ormicroRNA(s) changes (e.g., increases or decreases relative to a controlsample (e.g., tissue or cell) known to be sensitive or resistant to thetreatment, as is discussed above in connection with the first aspect ofthe invention). In an embodiment, the instructions further indicate thata change in the level of expression of the gene(s) or microRNA(s)relative to the expression of the gene(s) or microRNA(s) in a controlsample (e.g., a cell or tissue known to be sensitive or resistant to thetreatment) indicates a change in sensitivity of the patient to thetreatment (e.g., a decrease in the level of expression of a gene ormicroRNA known to be expressed in cells sensitive to the treatmentindicates that the patient is becoming resistant to the treatment or islikely to become resistant to the treatment, and vice versa).

In another embodiment, the kit can be utilized to determine a patient'sresistance or sensitivity to radiation therapy or the chemotherapyagents Vincristine, Cisplatin, Adriamycin, Etoposide, Azaguanine,Aclarubicin, Mitoxantrone, Paclitaxel, Mitomycin, Gemcitabine, Taxotere,Dexamethasone, Methylprednisolone, Ara-C, Methotrexate, Bleomycin,Methyl-GAG, Rituximab, PXD101 (a histone deacetylase (HDAC) inhibitor),5-Aza-2′-deoxycytidine (Decitabine), Melphalan, IL4-PE38 fusion protein,IL13-PE38QQR fusion protein (cintredekin besudotox), Valproic acid(VPA), All-trans retinoic acid (ATRA), Cytoxan, Topotecan (Hycamtin),Suberoylanilide hydroxamic acid (SAHA, vorinostat, Zolinza),Depsipeptide (FR901229), Bortezomib, Leukeran, Fludarabine, Vinblastine,Busulfan, Dacarbazine, Oxaliplatin, Hydroxyurea, Tegafur, Daunorubicin,Bleomycin, Estramustine, Chlorambucil, Mechlorethamine, Streptozocin,Carmustine, Lomustine, Mercaptopurine, Teniposide, Dactinomycin,Tretinoin, Sunitinib, SPC2996, Ifosfamide, Tamoxifen, Floxuridine,Irinotecan, and Satraplatin by measuring the level of expression of oneor more of the genes or microRNAs set forth in the first aspect of theinvention and known to change (e.g., to increase or decrease) in apatient sensitive to treatment with these agents (e.g., a patient isdetermined to be sensitive, or likely to be sensitive, to the indicatedtreatment if the level of expression of one or more of the gene(s) ormicroRNA(s) increases or decreases relative to the level of expressionof the gene(s) or microRNA(s) in a control sample (e.g., a cell ortissue) in which increased or decreased expression of the gene(s) ormicroRNA(s) indicates sensitivity to the treatment, and vice versa).

In another embodiment, the nucleic acid molecules are characterized bytheir ability to specifically identify nucleic acid moleculescomplementary to the genes or microRNAs in a sample collected from acancer patient.

In a fourth aspect, the invention features a kit that includes asingle-stranded nucleic acid molecule (e.g., one or a plurality thereof;e.g., a deoxyribonucleic acid molecule or a ribonucleic acid molecule)that is substantially complementary to (e.g., that has at least 80%,90%, 95% 97%, 99%, or 100% identical to the complement of) or that issubstantially identical to (e.g., that has at least 80%, 90%, 95% 97%,99%, or 100% identity to) at least 5 consecutive nucleotides (morepreferably at least 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70,75, 80, 85, 90, 95, 100, 150, 200, 250, 300, or more consecutivenucleotides; the nucleic acid can also be 5-20, 25, 5-50, 50-100, orover 100 consecutive nucleotides long) of at least one of the microRNAs(e.g., at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80,90, 100, or more of the microRNAs) set forth in the first aspect of theinvention, such that the single-stranded nucleic acid molecule issufficient for measuring the level of expression of the microRNA(s) byallowing specific hybridization between the single-stranded nucleic acidmolecule and a microRNA, or a complement thereof. The kit furtherincludes instructions for applying nucleic acid molecules collected froma sample from a cancer patient (e.g., from a cell of the patient),determining the level of expression of the microRNA(s) hybridized to thesingle-stranded nucleic acid, and determining the patient's sensitivityto a treatment for cancer when use of the kit indicates that the levelof expression of microRNA(s) changes (e.g., increases or decreasesrelative to a control sample (e.g., tissue or cell) known to besensitive or resistant to the treatment, as is discussed above inconnection with the first aspect of the invention). In an embodiment,the instructions further indicate that a change in the level ofexpression of microRNA(s) relative to the expression of microRNA(s) in acontrol sample (e.g., a cell or tissue known to be sensitive orresistant to the treatment) indicates a change in sensitivity of thepatient to the treatment (e.g., a decrease in the level of expression ofa microRNA known to be expressed in cells sensitive to the treatmentindicates that the patient is becoming resistant to the treatment or islikely to become resistant to the treatment, and vice versa).

In another embodiment, the kit can be utilized to determine a patient'sresistance or sensitivity to radiation therapy or the chemotherapyagents Vincristine, Cisplatin, Adriamycin, Etoposide, Azaguanine,Aclarubicin, Mitoxantrone, Paclitaxel, Mitomycin, Gemcitabine, Taxotere,Dexamethasone, Methylprednisolone, Ara-C, Methotrexate, Bleomycin,Methyl-GAG, Rituximab, PXD101 (a histone deacetylase (HDAC) inhibitor),5-Aza-2′-deoxycytidine (Decitabine), Melphalan, IL4-PE38 fusion protein,IL13-PE38QQR fusion protein (cintredekin besudotox), Valproic acid(VPA), All-trans retinoic acid (ATRA), Cytoxan, Topotecan (Hycamtin),Suberoylanilide hydroxamic acid (SAHA, vorinostat, Zolinza),Depsipeptide (FR901229), Bortezomib, Leukeran, Fludarabine, Vinblastine,Busulfan, Dacarbazine, Oxaliplatin, Hydroxyurea, Tegafur, Daunorubicin,Bleomycin, Estramustine, Chlorambucil, Mechlorethamine, Streptozocin,Carmustine, Lomustine, Mercaptopurine, Teniposide, Dactinomycin,Tretinoin, Sunitinib, SPC2996, Ifosfamide, Tamoxifen, Floxuridine,Irinotecan, and Satraplatin by measuring the level of expression of oneor more of the microRNAs set forth in the first aspect of the inventionand known to change (e.g., to increase or decrease) in a patientsensitive to treatment with these agents (e.g., a patient is determinedto be sensitive, or likely to be sensitive, to the indicated treatmentif the level of expression of one or more of the microRNA(s) increasesor decreases relative to the level of expression of the microRNA(s) in acontrol sample (e.g., a cell or tissue) in which increased or decreasedexpression of the or microRNA(s) indicates sensitivity to the treatment,and vice versa).

In another embodiment, the nucleic acid molecules are characterized bytheir ability to specifically identify nucleic acid moleculescomplementary to the microRNAs in a sample collected from a cancerpatient.

In a fifth aspect, the invention features a method of identifyingbiomarkers (e.g., genes and microRNAs) indicative of sensitivity of acancer patient to a treatment for cancer by obtaining pluralities ofmeasurements of the expression level of a gene or microRNA (e.g., bydetection of the expression of a gene or microRNA using a single probeor by using multiple probes directed to a single gene or microRNA) indifferent cell types and measurements of the growth of those cell typesin the presence of a treatment for cancer relative to the growth of thecell types in the absence of the treatment for cancer; correlating eachplurality of measurements of the expression level of the gene ormicroRNA in cells with the growth of the cells to obtain a correlationcoefficient; selecting the median correlation coefficient calculated forthe gene or microRNA; and identifying the gene or microRNA as abiomarker for use in determining the sensitivity of a cancer patient tosaid treatment for cancer if said median correlation coefficient exceeds0.3 (preferably the gene or microRNA is identified as a biomarker for apatient's sensitivity to a treatment if the correlation coefficientexceeds 0.4, 0.5, 0.6, 0.7, 0.8. 0.9, 0.95, or 0.99 or more). In anembodiment, the method is performed in the presence of a secondtreatment.

In a sixth aspect, the invention features a method of determiningsensitivity of a patient (e.g., a cancer patient) to a treatment forcancer by obtaining a measurement of the level of expression of a geneor microRNA in a sample (e.g., a cell or tissue) from the patient;applying a model predictive of sensitivity to a treatment for cancer tothe measurement, in which the model is developed using an algorithmselected from the group consisting of linear sums, nearest neighbor,nearest centroid, linear discriminant analysis, support vector machines,and neural networks; and determining whether or not the patient will beresponsive to the treatment for cancer. In an embodiment, themeasurement is obtained by measuring the level of expression of any ofthe genes or microRNAs set forth in the first aspect of the invention ina cell known to be sensitive or resistant to the treatment. In anotherembodiment, the method is performed in the presence of a secondtreatment. In another embodiment, the model combines the outcomes oflinear sums, linear discriminant analysis, support vector machines,neural networks, k-nearest neighbors, and nearest centroids, or themodel is cross-validated using a random sample of multiple measurements.In another embodiment, treatment, e.g., a compound, has previouslyfailed to show efficacy in a patient. In several embodiments, the linearsum is compared to a sum of a reference population with knownsensitivity; the sum of a reference population is the median of the sumsderived from the population members' biomarker gene expression. Inanother embodiment, the model is derived from the components of a dataset obtained by independent component analysis or is derived from thecomponents of a data set obtained by principal component analysis. Inanother embodiment, the invention features a kit, apparatus, andsoftware used to implement the method of the sixth aspect of theinvention.

In several embodiments of all aspects of the invention, the level ofexpression of the gene(s) is determined by measuring the level of mRNAtranscribed from the gene(s), by detecting the level of a proteinproduct of the gene(s), or by detecting the level of the biologicalactivity of a protein product of the gene(s). In further embodiments ofall aspects of the invention, an increase or decrease in the expressionlevel of the gene(s) or microRNA(s), relative to the expression level ofthe gene(s) or microRNA(s) in a cell or tissue sensitive to thetreatment, indicates increased sensitivity of the cancer patient to thetreatment. Alternatively, an increase or decrease in the expressionlevel of the gene(s) or microRNA(s), relative to the expression level ofthe gene(s) or microRNA(s) in a cell or tissue resistant to thetreatment, indicates increased resistance of the cancer patient to thetreatment. In another embodiment of all aspects of the invention, thecell is a cancer cell. In another embodiment of all aspects of theinvention, the expression level of the gene(s) is measured using aquantitative reverse transcription-polymerase chain reaction (qRT-PCR).In an embodiment of all aspects of the invention, the level ofexpression of two of the listed genes or microRNAs is measured, morepreferably the level of expression of three, four, five, six, seven,eight, nine, or ten of the listed genes or microRNAs is measured, andmost preferably twenty, thirty, forty, fifty, sixty, seventy, eighty,ninety, or one hundred or more of the listed genes or microRNAs ismeasured. In another embodiment of all aspects of the invention, theexpression level of the gene(s) or microRNA(s) is determined using thekit of the third or fourth aspects of the invention.

In another embodiment of all aspects of the invention, the treatment isradiation therapy or a compound, such as a chemotherapy agent selectedfrom the group consisting of Vincristine, Cisplatin, Adriamycin,Etoposide, Azaguanine, Aclarubicin, Mitoxantrone, Paclitaxel, Mitomycin,Gemcitabine, Taxotere, Dexamethasone, Methylprednisolone, Ara-C,Methotrexate, Bleomycin, Methyl-GAG, Rituximab, PXD101 (a histonedeacetylase (HDAC) inhibitor), 5-Aza-2′-deoxycytidine (Decitabine),Melphalan, IL4-PE38 fusion protein, IL13-PE38QQR fusion protein(cintredekin besudotox), Valproic acid (VPA), All-trans retinoic acid(ATRA), Cytoxan, Topotecan (Hycamtin), Suberoylanilide hydroxamic acid(SAHA, vorinostat, Zolinza), Depsipeptide (FR901229), Bortezomib,Leukeran, Fludarabine, Vinblastine, Busulfan, Dacarbazine, Oxaliplatin,Hydroxyurea, Tegafur, Daunorubicin, Bleomycin, Estramustine,Chlorambucil, Mechlorethamine, Streptozocin, Carmustine, Lomustine,Mercaptopurine, Teniposide, Dactinomycin, Tretinoin, Sunitinib, SPC2996,Ifosfamide, Tamoxifen, Floxuridine, Irinotecan, and Satraplatin. Inanother embodiment of all aspects of the invention, the treatment haspreviously failed to show effect in a subject (e.g., a subject selectedfrom a subpopulation determined to be sensitive to the treatment, asubject selected from a subpopulation predicted to die withouttreatment, a subject selected from a subpopulation predicted to havedisease symptoms without treatment, a subject selected from asubpopulation predicted to be cured without treatment.

In another embodiment of all aspects of the invention, the treatment is,e.g., administration of a compound, a protein, an antibody, anoligonucleotide, a chemotherapeutic agent, or radiation to a patient. Inan embodiment of all aspects of the invention, the treatment is, e.g., achemotherapeutic agent, such as, e.g., Vincristine, Cisplatin,Azaguanine, Etoposide, Adriamycin, Aclarubicin, Mitoxantrone, Mitomycin,Paclitaxel, Gemcitabine, Taxotere, Dexamethasone, Ara-C,Methylprednisolone, Methotrexate, Bleomycin, Methyl-GAG, Carboplatin,5-FU (5-Fluorouracil), a histone deacetylase (HDAC) inhibitor such asPXD101, 5-Aza-2′-deoxycytidine (Decitabine), alpha emitters such asastatine-211, bismuth-212, bismuth-213, lead-212, radium-223,actinium-225, and thorium-227, beta emitters such as tritium,strontium-90, cesium-137, carbon-11, nitrogen-13, oxygen-15,fluorine-18, iron-52, cobalt-55, cobalt-60, copper-61, copper-62,copper-64, zinc-62, zinc-63, arsenic-70, arsenic-71, arsenic-74,bromine-76, bromine-79, rubidium-82, yttrium-86, zirconium-89,indium-110, iodine-120, iodine-124, iodine-129, iodine-131, iodine-125,xenon-122, technetium-94m, technetium-94, technetium-99m, andtechnetium-99, gamma emitters such as cobalt-60, cesium-137, andtechnetium-99m, Alemtuzumab, Daclizumab, Rituximab (e.g., MABTHERA™),Trastuzumab (e.g., HERCEPTIN™), Gemtuzumab, Ibritumomab, Edrecolomab,Tositumomab, CeaVac, Epratuzumab, Mitumomab, Bevacizumab, Cetuximab,Edrecolomab, Lintuzumab, MDX-210, IGN-01, MDX-010, MAb, AME, ABX-EGF,EMD 72 000, Apolizumab, Labetuzumab, ior-t1, MDX-220, MRA, H-11 scFv,Oregovomab, huJ591 MAb, BZL, Visilizumab, TriGem, TriAb, R3, MT-201,G-250, unconjugated, ACA-125, Onyvax-105, CDP-860, BrevaRex MAb, AR54,IMC-1C11, GlioMAb-H, ING-1, Anti-LCG MAbs, MT-103, KSB-303, Therex,KW-2871, Anti-HMI.24, Anti-PTHrP, 2C4 antibody, SGN-30, TRAIL-RI MAb,CAT, Prostate cancer antibody, H22xKi-4, ABX-MA1, Imuteran, Monopharm-C,Acivicin, Aclarubicin, Acodazole Hydrochloride, Acronine, Adozelesin,Adriamycin, Aldesleukin, Altretamine, Ambomycin, A. metantrone Acetate,Aminoglutethimide, Amsacrine, Anastrozole, Anthramycin, Asparaginase,Asperlin, Azacitidine, Azetepa, Azotomycin, Batimastat, Benzodepa,Bicalutamide, Bisantrene Hydrochloride, Bisnafide Dimesylate, Bizelesin,Bleomycin Sulfate, Brequinar Sodium, Bropirimine, Busulfan,Cactinomycin, Calusterone, Camptothecin, Caracemide, Carbetimer,Carboplatin, Carmustine, Carubicin Hydrochloride, Carzelesin,Cedefingol, Chlorambucil, Cirolemycin, Cisplatin, Cladribine,Combretestatin A-4, Crisnatol Mesylate, Cyclophosphamide, Cytarabine,Dacarbazine, DACA (N-[2-(Dimethyl-amino)ethyl]acridine-4-carboxamide),Dactinomycin, Daunorubicin Hydrochloride, Daunomycin, Decitabine,Dexormaplatin, Dezaguanine, Dezaguanine Mesylate, Diaziquone, Docetaxel,Dolasatins, Doxorubicin, Doxorubicin Hydrochloride, Droloxifene,Droloxifene Citrate, Dromostanolone Propionate, Duazomycin, Edatrexate,Eflomithine Hydrochloride, Ellipticine, Elsamitrucin, Enloplatin,Enpromate, Epipropidine, Epirubicin Hydrochloride, Erbulozole,Esorubicin Hydrochloride, Estramustine, Estramustine Phosphate Sodium,Etanidazole, Ethiodized Oil I 131, Etoposide, Etoposide Phosphate,Etoprine, Fadrozole Hydrochloride, Fazarabine, Fenretinide, Floxuridine,Fludarabine Phosphate, Fluorouracil, 5-FdUMP, Fluorocitabine,Fosquidone, Fostriecin Sodium, Gemcitabine, Gemcitabine Hydrochloride,Gold Au 198, Homocamptothecin, Hydroxyurea, Idarubicin Hydrochloride,Ifosfamide, Ilmofosine, Interferon Alfa-2a, Interferon Alfa-2b,Interferon Alfa-n1, Interferon Alfa-n3, Interferon Beta-I a, InterferonGamma-I b, Iproplatin, Irinotecan Hydrochloride, Lanreotide Acetate,Letrozole, Leuprolide Acetate, Liarozole Hydrochloride, LometrexolSodium, Lomustine, Losoxantrone Hydrochloride, Masoprocol, Maytansine,Mechlorethamine Hydrochloride, Megestrol Acetate, Melengestrol Acetate,Melphalan, Menogaril, Mercaptopurine, Methotrexate, Methotrexate Sodium,Metoprine, Meturedepa, Mitindomide, Mitocarcin, Mitocromin, Mitogillin,Mitomalcin, Mitomycin, Mitosper, Mitotane, Mitoxantrone Hydrochloride,Mycophenolic Acid, Nocodazole, Nogalamycin, Ormaplatin, Oxisuran,Paclitaxel, Pegaspargase, Peliomycin, Pentamustine, PeploycinSulfate,Perfosfamide, Pipobroman, Piposulfan, Piroxantrone Hydrochloride,Plicamycin, Plomestane, Porfimer Sodium, Porfiromycin, Prednimustine,Procarbazine Hydrochloride, Puromycin, Puromycin Hydrochloride,Pyrazofurin, Rhizoxin, Rhizoxin D, Riboprine, Rogletimide, Safingol,Safingol Hydrochloride, Semustine, Simtrazene, Sparfosate Sodium,Sparsomycin, Spirogermanium Hydrochloride, Spiromustine, Spiroplatin,Streptonigrin, Streptozocin, Strontium Chloride Sr 89, Sulofenur,Talisomycin, Taxane, Taxoid, Tecogalan Sodium, Tegafur, TeloxantroneHydrochloride, Temoporfin, Teniposide, Teroxirone, Testolactone,Thiamiprine, Thioguanine, Thiotepa, Thymitaq, Tiazofurin, Tirapazamine,Tomudex, TOP53, Topotecan Hydrochloride, Toremifene Citrate, TrestoloneAcetate, Triciribine Phosphate, Trimetrexate, Trimetrexate Glucuronate,Triptorelin, Tubulozole Hydrochloride, Uracil Mustard, Uredepa,Vapreotide, Verteporfin, Vinblastine, Vinblastine Sulfate, Vincristine,Vincristine Sulfate, Vindesine, Vindesine Sulfate, Vinepidine Sulfate,Vinglycinate Sulfate, Vinleurosine Sulfate, Vinorelbine Tartrate,Vinrosidine Sulfate, Vinzolidine Sulfate, Vorozole, Zeniplatin,Zinostatin, Zorubicin Hydrochloride, 2-Chlorodeoxyadenosine, 2′Deoxyformycin, 9-aminocamptothecin, raltitrexed,N-propargyl-5,8-dideazafolic acid,2chloro-2′-arabino-fluoro-2′-deoxyadenosine, 2-chloro-2′-deoxyadenosine,anisomycin, trichostatin A, hPRL-G129R, CEP-751, linomide, sulfurmustard, nitrogen mustard (mechlor ethamine), cyclophosphamide,melphalan, chlorambucil, ifosfamide, busulfan, N-methyl-Nnitrosourea(MNU), N,N′-Bis(2-chloroethyl)-N-nitrosourea (BCNU),N-(2-chloroethyl)-N′ cyclohexyl-N-nitrosourea (CCNU),N-(2-chloroethyl)-N′-(trans-4-methylcyclohexyl-N-nitrosourea (MeCCNU),N-(2-chloroethyl)-N′-(diethyl)ethylphosphonate-N-nitrosourea(fotemustine), streptozotocin, diacarbazine (DTIC), mitozolomide,temozolomide, thiotepa, mitomycin C, AZQ, adozelesin, Cisplatin,Carboplatin, Ormaplatin, Oxaliplatin, C1-973, DWA 2114R, JM216, JM335,Bis(platinum), tomudex, azacitidine, cytarabine, gemcitabine,6-Mercaptopurine, 6-Thioguanine, Hypoxanthine, teniposide 9-aminocamptothecin, Topotecan, CPT-11, Doxorubicin, Daunomycin, Epirubicin,darubicin, mitoxantrone, losoxantrone, Dactinomycin (Actinomycin D),amsacrine, pyrazoloacridine, all-trans retinol,14-hydroxy-retro-retinol, all-trans retinoic acid,N-(4-Hydroxyphenyl)retinamide, 13-cis retinoic acid, 3-Methyl TTNEB,9-cis retinoic acid, fludarabine (2-F-ara-AMP), 2-chlorodeoxyadenosine(2-Cda), 20-pi-1,25 dihydroxyvitamin D3,5-ethynyluracil, abiraterone,aclarubicin, acylfulvene, adecypenol, adozelesin, aldesleukin, ALL-TKantagonists, altretamine, ambamustine, amidox, amifostine,aminolevulinic acid, amrubicin, amsacrine, anagrelide, anastrozole,andrographolide, angiogenesis inhibitors, antagonist D, antagonist G,antarelix, anti-dorsalizing morphogenetic protein-1, antiandrogen,prostatic carcinoma, antiestrogen, antineoplaston, antisenseoligonucleotides, aphidicolin glycinate, apoptosis gene modulators,apoptosis regulators, apurinic acid, ara-CDP-DL-PTBA, argininedeaminase,asulacrine, atamestane, atrimustine, axinastatin 1, axinastatin 2,axinastatin 3, azasetron, azatoxin, azatyrosine, baccatin IIIderivatives, balanol, batimastat, BCR/ABL antagonists, benzochlorins,benzoylstaurosporine, beta lactam derivatives, beta-alethine,betaclamycin B, betulinic acid, bFGF inhibitor, bicalutamide,bisantrene, bisaziridinylspermine, bisnafide, bistratene A, bizelesin,breflate, bleomycin A2, bleomycin B2, bropirimine, budotitane,buthionine sulfoximine, calcipotriol, calphostin C, camptothecinderivatives (e.g., 10-hydroxy-camptothecin), canarypox IL-2,capecitabine, carboxamide-amino-triazole, carboxyamidotriazole, CaRestM3, CARN 700, cartilage derived inhibitor, carzelesin, casein kinaseinhibitors (ICOS), castanospermine, cecropin B, cetrorelix, chlorins,chloroquinoxaline sulfonamide, cicaprost, cis-porphyrin, cladribine,clomifene analogues, clotrimazole, collismycin A, collismycin B,combretastatin A4, combretastatin analogue, conagenin, crambescidin 816,crisnatol, cryptophycin 8, cryptophycin A derivatives, curacin A,cyclopentanthraquinones, cycloplatam, cypemycin, cytarabine ocfosfate,cytolytic factor, cytostatin, dacliximab, decitabine, dehydrodidemnin B,2′deoxycoformycin (DCF), deslorelin, dexifosfamide, dexrazoxane,dexverapamil, diaziquone, didemnin B, didox, diethylnorspermine,dihydro-5-azacytidine, 9-dihydrotaxol, dioxamycin, diphenylspiromustine, discodermolide, docosanol, dolasetron, doxifluridine,droloxifene, dronabinol, duocarmycin SA, ebselen, ecomustine,edelfosine, edrecolomab, eflomithine, elemene, emitefur, epirubicin,epothilones (A, R═H, B, R═Me), epithilones, epristeride, estramustineanalogue, estrogen agonists, estrogen antagonists, etanidazole,etoposide, etoposide 4′-phosphate (etopofos), exemestane, fadrozole,fazarabine, fenretinide, filgrastim, finasteride, flavopiridol,flezelastine, fluasterone, fludarabine, fluorodaunorunicinhydrochloride, forfenimex, formestane, fostriecin, fotemustine,gadolinium texaphyrin, gallium nitrate, galocitabine, ganirelix,gelatinase inhibitors, gemcitabine, glutathione inhibitors, hepsulfam,heregulin, hexamethylene bisacetamide, homoharringtonine (HHT),hypericin, ibandronic acid, idarubicin, idoxifene, idramantone,ilmofosine, ilomastat, imidazoacridones, imiquimod, immunostimulantpeptides, insulin-like growth factor-1 receptor inhibitor, interferonagonists, interferons, interleukins, iobenguane, iododoxorubicin,4-ipomeanol, irinotecan, iroplact, irsogladine, isobengazole,isohomohalicondrin B, itasetron, jasplakinolide, kahalalide F,lamellarin-N triacetate, lanreotide, leinamycin, lenograstim, lentinansulfate, leptolstatin, letrozole, leukemia inhibiting factor, leukocytealpha interferon, leuprolide, estrogen, and progesterone combinations,leuprorelin, levamisole, liarozole, linear polyamine analogue,lipophilic disaccharide peptide, lipophilic platinum compounds,lissoclinamide 7, lobaplatin, lombricine, lometrexol, lonidamine,losoxantrone, lovastatin, loxoribine, lurtotecan, lutetium texaphyrin,lysofylline, lytic peptides, maytansine, mannostatin A, marimastat,masoprocol, maspin, matrilysin inhibitors, matrix metalloproteinaseinhibitors, menogaril, merbarone, meterelin, methioninase,metoclopramide, MIF inhibitor, ifepristone, miltefosine, mirimostim,mismatched double stranded RNA, mithracin, mitoguazone, mitolactol,mitomycin analogues, mitonafide, mitotoxin fibroblast growthfactor-saporin, mitoxantrone, mofarotene, molgramostim, monoclonalantibody, human chorionic gonadotrophin, monophosphoryl lipid A andmyobacterium cell wall skeleton combinations, mopidamol, multiple drugresistance gene inhibitor, multiple tumor suppressor 1-based therapy,mustard anticancer agent, mycaperoxide B, mycobacterial cell wallextract, myriaporone, N-acetyldinaline, N-substituted benzamides,nafarelin, nagrestip, naloxone and pentazocine combinations, napavin,naphterpin, nartograstim, nedaplatin, nemorubicin, neridronic acid,neutral endopeptidase, nilutamide, nisamycin, nitric oxide modulators,nitroxide antioxidant, nitrullyn, 06-benzylguanine, octreotide,okicenone, oligonucleotides, onapristone, ondansetron, ondansetron,oracin, oral cytokine inducer, ormaplatin, osaterone, oxaliplatin,oxaunomycin, paclitaxel analogues, paclitaxel derivatives, palauamine,palmitoylrhizoxin, pamidronic acid, panaxytriol, panomifene, parabactin,pazelliptine, pegaspargase, peldesine, pentosan polysulfate sodium,pentostatin, pentrozole, perflubron, perfosfamide, perillyl alcohol,phenazinomycin, phenylacetate, phosphatase inhibitors, picibanil,pilocarpine hydrochloride, pirarubicin, piritrexim, placetin A, placetinB, plasminogen activator inhibitor, platinum complex, platinumcompounds, platinum-triamine complex, podophyllotoxin, porfimer sodium,porfiromycin, propyl bis-acridone, prostaglandin J2, proteasomeinhibitors, protein A-based immune modulator, protein kinase Cinhibitor, protein kinase C inhibitors, microalgal, protein tyrosinephosphatase inhibitors, purine nucleoside phosphorylase inhibitors,purpurins, pyrazoloacridine, pyridoxylated hemoglobin polyoxyethyleneconjugate, raf antagonists, raltitrexed, ramosetron, ras farnesylprotein transferase inhibitors, ras inhibitors, ras-GAP inhibitor,retelliptine demethylated, rhenium Re 186 etidronate, rhizoxin,ribozymes, RII retinamide, rogletimide, rohitukine, romurtide,roquinimex, rubiginone B 1, ruboxyl, safingol, saintopin, SarCNU,sarcophytol A, sargramostim, Sdi 1 mimetics, semustine, senescencederived inhibitor 1, sense oligonucleotides, signal transductioninhibitors, signal transduction modulators, single chain antigen bindingprotein, sizofuran, sobuzoxane, sodium borocaptate, sodiumphenylacetate, solverol, somatomedin binding protein, sonermin,sparfosic acid, spicamycin D, spiromustine, splenopentin, spongistatin1, squalamine, stem cell inhibitor, stem-cell division inhibitors,stipiamide, stromelysin inhibitors, sulfinosine, superactive vasoactiveintestinal peptide antagonist, suradista, suramin, swainsonine,synthetic glycosaminoglycans, tallimustine, tamoxifen methiodide,tauromustine, tazarotene, tecogalan sodium, tegafur, tellurapyrylium,telomerase inhibitors, temoporfin, temozolomide, teniposide,tetrachlorodecaoxide, tetrazomine, thaliblastine, thalidomide,thiocoraline, thrombopoietin, thrombopoietin mimetic, thymalfasin,thymopoietin receptor agonist, thymotrinan, thyroid stimulating hormone,tin ethyl etiopurpurin, tirapazamine, titanocene dichloride, topotecan,topsentin, toremifene, totipotent stem cell factor, translationinhibitors, tretinoin, triacetyluridine, triciribine, trimetrexate,triptorelin, tropisetron, turosteride, tyrosine kinase inhibitors,tyrphostins, UBC inhibitors, ubenimex, urogenital sinus-derived growthinhibitory factor, urokinase receptor antagonists, vapreotide, variolinB, vector system, erythrocyte gene therapy, velaresol, veramine,verdins, verteporfin, vinorelbine, vinxaltine, vitaxin, vorozole,zanoterone, zeniplatin, zilascorb, or zinostatin stimalamer. In anotherembodiment of all aspects of the invention, a second treatment isutilized to determine gene expression in a sample from the patient.

In another embodiment of all aspects of the invention, the gene isselected from the group consisting of ABL1, ACTB, ACTN1, ACTN4, ACTR2,ADA, ADAM9, ADAMTS1, ADD1, ADORA2A, AF1Q, AIF1, AKAP1, AKAP13, AKR1B1,AKR1C1, AKT1, ALDH2, ALDH3A1, ALDOC, ALG5, ALMS1, ALOX15B, AMIGO2,AMPD2, AMPD3, ANAPC5, ANP32A, ANP32B, ANPEP, ANXA1, ANXA2, AP1G2,APOBEC3B, APRT, ARHE, ARHGAP15, ARHGAP25, ARHGDIB, ARHGEF6, ARL7, ASAH1,ASPH, ATF3, ATIC, ATOX1, ATP1B3, ATP2A2, ATP2A3, ATP5D, ATP5G2,ATP6V1B2, B2M, BASP1, BAX, BC008967, BCAT1, BCHE, BCL11B, BDNF, BHLHB2,BIN2, BLM, BLMH, BLVRA, BMI1, BNIP3, BRDT, BRRN1, BTN3A2, BTN3A3,C11orf2, C14orf139, C15orf25, C18orf10, C1orf24, C1orf29, C1orf38,C1QR1, C22orf18, C5orf13, C6orf32, CACNA1G, CACNB3, CALD1, CALM1,CALML4, CALU, CAP350, CAPG, CAPN2, CAPN3, CASP2, CASP6, CASP7, CAST,CBFB, CBLB, CBR1, CBX3, CCL2, CCL21, CCNA2, CCNB1IP1, CCND3, CCR7, CCR9,CCT5, CD151, CD1A, CD1B, CD1C, CD1D, CD1E, CD2, CD28, CD37, CD3D, CD3E,CD3G, CD3Z, CD44, CD47, CD53, CD59, CD6, CD63, CD81, CD8A, CD8B1, CD99,CDC10, CDCl₄B, CDH11, CDH2, CDKL5, CDKN2A, CDW52, CECR1, CENPB, CENTB1,CENTG2, CEP1, CG018, CHRNA3, CHS1, CIAPIN1, CKAP4, CKIP-1, CNN3, CNP,COL1A1, COL4A1, COL4A2, COL5A2, COL6A1, COL6A2, COPA, COPEB, CORO1A,CORO1C, COX7B, CPSF1, CRABP1, CREB3L1, CRIP2, CRK, CRY1, CSDA, CSPG2,CSRP1, CST3, CTBP1, CTGF, CTNNA1, CTSB, CTSC, CTSD, CTSL, CUGBP2, CUTC,CXCL1, CXCR4, CXorf9, CYFIP2, CYLD, CYR61, DATF1, DAZAP1, DBN1, DBT,DCTN1, DDOST, DDX18, DDX5, DGKA, DIAPH1, DIPA, DKC1, DKFZP434J154,DKFZP564C186, DKFZP564G2022, DKFZp564J157, DKFZP564K0822, DNAJC10,DNAPTP6, DOCK10, DOCK2, DPAGT1, DPEP2, DPYSL3, DSIPI, DUSP1, DUSP3,DXS9879E, DYRK2, E2F4, ECE1, ECM1, EEF1A1, EEF1B2, EEF1G, EFNB2, EHD2,EIF2S2, EIF3S2, EIF4B, EIF4G3, EIF5A, ELA2B, ELK3, EMP3, ENO2, EPAS1,EPB41L4B, ERCC2, ERG, ERP70, EVER1, EVI2A, EVL, EXT1, EZH2, F2R, FABP5,FAD104, FAM46A, FARSLA, FAT, FAU, FBL, FCGR2A, FCGR2C, FER1L3, FGFR1,FHL1, FHOD1, FKBP1A, FKBP9, FLII, FLJ10350, FLJ10539, FLJ10774,FLJ12270, FLJ13373, FLJ20859, FLJ21159, FLJ22457, FLJ35036, FLJ46603,FLNC, FLOT1, FMNL1, FN1, FNBP1, FOLH1, FOXF2, FSCN1, FSTL1, FTH1, FTL,FYB, FYN, GOS2, G6PD, GALIG, GALNT6, GAPD, GAS7, GATA2, GATA3, GFPT1,GIMAP5, GIT2, GJA1, GLRB, GLTSCR2, GLUL, GMDS, GMFG, GNA15, GNAI2, GNAQ,GNB2, GNB5, GOT2, GPNMB, GPR65, GPRASP1, GPSM3, GRP58, GSTM2, GTF3A,GTSE1, GYPC, GZMA, GZMB, H1F0, H1FX, H2AFX, H3F3A, HA-1, HCLS1, HEM1,HEXB, HIC, HIST1H4C, HK1, HLA-A, HLA-B, HLA-DRA, HMGA1, HMGB2, HMGN2,HMMR, HNRPA1, HNRPD, HNRPM, HOXA9, HPRT1, HRMT1L1, HSA9761, HSPA5,HSU79274, HTATSF1, HU6800, ICAM1, ICAM2, IER3, IFI16, IFI44, IFITM2,IFITM3, IFRG28, IGFBP2, IGFBP3, IGSF4, IL13RA2, IL21R, IL2RG, IL4R, IL6,IL6R, IL6ST, IL8, IMPDH2, INPP5D, INSIG1, IQGAP1, IQGAP2, IRS2, ITGA3,ITGA5, ITGB2, ITK, ITM2A, JAK1, JARID2, JUNB, K-ALPHA-1, KHDRBS1,KIAA0220, KLAA0355, KIAA0802, KIAA0877, KIAA0922, KIAA1078, KIAA1128,KIAA1393, KIFC1, KPNB1, LAIR1, LAMB1, LAMB3, LAMR1, LAPTM5, LAT, LBR,LCK, LCP1, LCP2, LDHB, LEF1, LEPRE1, LGALS1, LGALS9, LHFPL2, LMNB1, LNK,LOC54103, LOC55831, LOC81558, LOC94105, LONP, LOX, LOXL2, LPHN2, LPXN,LRMP, LRP12, LRRC5, LRRN3, LST1, LTB, LUM, LY9, LY96, M6PRBP1, MAD2L1BP,MAGEB2, MAL, MAN1A1, MAP1B, MAP1LC3B, MAP4K1, MAPK1, MAPRE1, MARCKS,MAZ, MCAM, MCL1, MCM5, MCM7, MDH2, MDK, MDN1, MEF2C, MFNG, MGC17330,MGC21654, MGC2744, MGC4083, MGC8721, MGC8902, MGLL, MIA, MICA, MLPH,MME, MMP2, MPHOSPH6, MPP1, MPZL1, MRP63, MRPL12, MRPS2, MSN, MT1E, MT1K,MUF1, MVP, MYB, MYC, MYL6, MYL9, MYO1B, NAP1L1, NAP1L2, NARF, NARS,NASP, NBL1, NCL, NCOR2, NDN, NDUFAB1, NDUFS6, NFIL3, NFKBIA, NID2,NIPA2, NK4, NME4, NME7, NNMT, NOL5A, NOL8, NOMO2, NOTCH1, NPC1, NQO1,NR1D2, NUCB2, NUDC, NUP210, NUP88, NVL, NXF1, OBFC1, OCRL, OGT,OK/SW-c1.56, OPTN, OXA1L, P2RX5, P4HA1, PACAP, PAF53, PAFAH1B3,PALM2-AKAP2, PAX6, PBEF1, PCBP2, PCCB, PEA15, PFDN5, PFN1, PFN2, PGAM1,PGK1, PHEMX, PHLDA1, PIM2, PITPNC1, PKM2, PLAC8, PLAGL1, PLAU, PLAUR,PLCB1, PLEK2, PLEKHC1, PLOD2, PLSCR1, PNAS-4, PNMA2, POLR2F, PON2,PPAP2B, PPIA, PPIF, PPP1R11, PPP2CB, PRF1, PRG1, PRIM1, PRKCA, PRKCB1,PRKCH, PRKCQ, PRKD2, PRNP, PRP19, PRPF8, PRPS1, PRSS11, PRSS23, PSCDBP,PSMB9, PSMC3, PSMC5, PSME2, PTGER4, PTGES2, PTMA, PTOV1, PTP4A3, PTPN7,PTPNS1, PTPRC, PTPRCAP, PTRF, PTS, PURA, PWP1, PYGL, QKI, RAB31,RAB3GAP, RAB7, RAB7L1, RAB9P40, RAC2, RAFTLIN, RAG2, RALY, RAP1B,RASGRP2, RBMX, RBPMS, RCN1, REA, RFC3, RFC5, RGC32, RGS3, RHOC, RHOH,RIMS3, RIOK3, RIPK2, RIS1, RNASE6, RNF144, RNPS1, RPL10, RPL10A, RPL11,RPL12, RPL13, RPL13A, RPL17, RPL18, RPL18A, RPL24, RPL3, RPL32, RPL36A,RPL39, RPL7, RPL9, RPLP0, RPLP2, RPS10, RPS11, RPS15, RPS15A, RPS19,RPS2, RPS23, RPS24, RPS25, RPS27, RPS28, RPS4X, RPS4Y1, RPS6, RPS7,RPS9, RRAS, RRAS2, RRBP1, RRM2, RUNX1, RUNX3, S100A13, S100A4, SART3,SATB1, SCAP1, SCARB1, SCARB2, SCN3A, SCTR, SEC31L2, SEC61G, SELL,SELPLG, SEMA4G, SEPT6, SEPT10, SEPW1, SERPINA1, SERPINB1, SERPINB6,SFRS3, SFRS5, SFRS6, SFRS7, SH2D1A, SH3GL3, SH3TC1, SHD1, SHFM1, SHMT2,SIAT1, SKB1, SKP2, SLA, SLC1A4, SLC20A1, SLC25A15, SLC25A5, SLC39A14,SLC39A6, SLC43A3, SLC4A2, SLC7A11, SLC7A6, SMA3, SMAD3, SMARCD3, SMOX,SMS, SND1, SNRPA, SNRPB, SNRPB2, SNRPE, SNRPF, SOD2, SOX4, SP140,SPANXC, SPARC, SPI1, SRF, SRM, SRRM1, SSA2, SSBP2, SSRP1, SSSCA1, STAG3,STAT1, STAT4, STAT5A, STC1, STC2, STMN1, STOML2, SUI1, T3JAM, TACC1,TACC3, TAF5, TAGLN, TAL1, TAP1, TARP, TBCA, TCF12, TCF4, TCF7, TFDP2,TFPI, TFRC, TGFB1, TIMM17A, TIMP1, TJP1, TK2, TM4SF1, TM4SF2, TM4SF8,TM6SF1, TMEM2, TMEM22, TMSB10, TMSNB, TNFAIP3, TNFAIP8, TNFRSF10B,TNFRSF1A, TNFRSF7, TNIK, TNPO1, TOB1, TOMM20, TOP2A, TOX, TPK1, TPM2,TRA@, TRA1, TRAM2, TRB@, TRD@, TRIM, TRIM14, TRIM22, TRIM28, TRIP13,TRPV2, TUBA3, TUBGCP3, TUFM, TUSC3, TXN, TXNDC5, UBASH3A, UBB, UBC,UBE2A, UBE2L6, UBE2S, UCHL1, UCK2, UCP2, UFD1L, UGCG, UGDH, UGT2B17,ULK2, UMPS, UNG, UROD, USP34, USP4, USP7, VASP, VAV1, VIM, VLDLR, VWF,WARS, WASPIP, WBSCR20A, WBSCR20C, WHSC1, WNT5A, XPO1, ZAP128, ZAP70,ZFP36L1, ZNF32, ZNF335, ZNF593, ZNFN1A1, or ZYX.

The nucleic acid sequence of each listed genes is publicly availablethrough the GenBank or RefSeq database(http://www.ncbi.nlm.nih.gov/sites/gquery). The gene sequences are alsoincluded as part of the HG-U133A GeneChip from Affymetrix, Inc.

“Resistant” or “resistance” as used herein means that a cell, a tumor, apatient (e.g., a human), or a living organism is able to withstandtreatment, e.g., with a compound, such as a chemotherapeutic agent, orradiation treatment, in that the treatment inhibits the growth of acell, e.g., a cancer cell, in vitro or in a tumor, patient, or livingorganism by less than 10%, 20%, 30%, 40%, 50%, 60%, or 70% relative tothe growth of a similar cell not exposed to the treatment. Resistance totreatment can be determined by a cell-based assay that measures thegrowth of treated cells as a function of the cells' absorbance of anincident light beam as used to perform the NCI60 assays describedherein. In this example, greater absorbance indicates greater cellgrowth, and thus, resistance to the treatment. A reduction in growthindicates more resistance to a treatment. By “chemoresistant” or“chemoresistance” is meant resistance to a compound.

“Sensitive” or “sensitivity” as used herein means that a cell, a tumor,a patient (e.g., a human), or a living organism is responsive totreatment, e.g., with a compound, such as a chemotherapeutic agent, orradiation treatment, in that the treatment inhibits the growth of acell, e.g., a cancer cell, in vitro or in a tumor, patient, or livingorganism by 70%, 80%, 90%, 95%, 99%, or 100%. Sensitivity to treatmentmay be determined by a cell-based assay that measures the growth oftreated cells as a function of the cells' absorbance of an incidentlight beam as used to perform the NCI60 assays described herein. In thisexample, lesser absorbance indicates reduced cell growth, and thus,sensitivity to the treatment. A greater reduction in growth indicatesmore sensitivity to the treatment. By “chemosensitive” or“chemosensitivity” is meant sensitivity to a compound.

“Complement” of a nucleic acid sequence or a “complementary” nucleicacid sequence as used herein refers to an oligonucleotide which is in“antiparallel association” when it is aligned with the nucleic acidsequence such that the 5′ end of one sequence is paired with the 3′ endof the other. Nucleotides and other bases can have complements and maybe present in complementary nucleic acids. Bases not commonly found innatural nucleic acids that can be included in the nucleic acids of thepresent invention include, for example, inosine and 7-deazaguanine.“Complementarity” may not be perfect; stable duplexes of complementarynucleic acids can contain mismatched base pairs or unmatched bases.Skilled artisans can determine duplex stability empirically consideringa number of variables including, for example, the length of theoligonucleotide, percent concentration of cytosine and guanine bases inthe oligonucleotide, ionic strength, and incidence of mismatched basepairs. Typically, complementarity is determined by comparing contiguousnucleic acid sequences.

When complementary nucleic acid sequences form a stable duplex, they aresaid to be “hybridized” or to “hybridize” to each other or it is saidthat “hybridization” has occurred. Nucleic acids are referred to asbeing “complementary” if they contain nucleotides or nucleotidehomologues that can form hydrogen bonds according to Watson-Crickbase-pairing rules (e.g., G with C, A with T, or A with U) or otherhydrogen bonding motifs such as, for example, diaminopurine with T,5-methyl C with G, 2-thiothymidine with A, inosine with C, andpseudoisocytosine with G. Anti-sense RNA can be complementary to otheroligonucleotides, e.g., mRNA.

“Biomarker” as used herein indicates a transcription product (e.g., RNA,such as an RNA primary transcript, mRNA, tRNA, rRNA, microRNA (miRNA),or complementary RNA or DNA (e.g., cDNA) strands thereof) or atranslation product (e.g., a polypeptide or metabolite thereof) of abiomarker gene, as defined herein, whose level of expression indicatesthe sensitivity or resistance of a cell (e.g., a cancer cell), tissue,organism, or patient (e.g., a human) to a treatment (e.g., chemotherapy,radiation therapy, or surgery).

“Compound” as used herein means a chemical or biological substance,e.g., a drug, a protein, an antibody, or an oligonucleotide, which canbe used to treat a disease or which has biological activity in vivo orin vitro. Compounds may or may not be approved by the U.S. Food and DrugAdministration (FDA). Preferred compounds include, e.g., chemotherapyagents that can inhibit cancer growth. Preferred chemotherapy agentsinclude, e.g., Vincristine, Cisplatin, Azaguanine, Etoposide,Adriamycin, Aclarubicin, Mitoxantrone, Mitomycin, Paclitaxel,Gemcitabine, Taxotere, Dexamethasone, Ara-C, Methylprednisolone,Methotrexate, Bleomycin, Methyl-GAG, Carboplatin, 5-FU (5-Fluorouracil),Rituximab (e.g., MABTHERA™), histone deacetylase (HDAC) inhibitors, and5-Aza-2′-deoxycytidine (Decitabine). Exemplary radioactivechemotherapeutic agents include compounds containing alpha emitters suchas astatine-211, bismuth-212, bismuth-213, lead-212, radium-223,actinium-225, and thorium-227, beta emitters such as tritium,strontium-90, cesium-137, carbon-11, nitrogen-13, oxygen-15,fluorine-18, iron-52, cobalt-55, cobalt-60, copper-61, copper-62,copper-64, zinc-62, zinc-63, arsenic-70, arsenic-71, arsenic-74,bromine-76, bromine-79, rubidium-82, yttrium-86, zirconium-89,indium-110, iodine-120, iodine-124, iodine-129, iodine-131, iodine-125,xenon-122, technetium-94m, technetium-94, technetium-99m, andtechnetium-99, and gamma emitters such as cobalt-60, cesium-137, andtechnetium-99m. Exemplary chemotherapeutic agents also includeantibodies such as Alemtuzumab, Daclizumab, Rituximab (e.g., MABTHERA™),Trastuzumab (e.g., HERCEPTIN™), Gemtuzumab, Ibritumomab, Edrecolomab,Tositumomab, CeaVac, Epratuzumab, Mitumomab, Bevacizumab, Cetuximab,Edrecolomab, Lintuzumab, MDX-210, IGN-101, MDX-010, MAb, AME, ABX-EGF,EMD 72 000, Apolizumab, Labetuzumab, ior-t1, MDX-220, MRA, H-11 scFv,Oregovomab, huJ591 MAb, BZL, Visilizumab, TriGem, TriAb, R3, MT-201,G-250, ACA-125, Onyvax-105, CDP-860, BrevaRex MAb, AR54, IMC-1C11,GlioMAb-H, ING-1, Anti-LCG MAbs, MT-103, KSB-303, Therex, KW-2871,Anti-HMI.24, Anti-PTHrP, 2C4 antibody, SGN-30, TRAIL-R1 MAb, CAT,Prostate cancer antibody, H22xKi-4, ABX-MA1, Imuteran, and Monopharm-C.Exemplary chemotherapeutic agents also include Acivicin; Aclarubicin;Acodazole Hydrochloride; Acronine; Adozelesin; Adriamycin; Aldesleukin;Altretamine; Ambomycin; A. metantrone Acetate; Aminoglutethimide;Amsacrine; Anastrozole; Anthramycin; Asparaginase; Asperlin;Azacitidine; Azetepa; Azotomycin; Batimastat; Benzodepa; Bicalutamide;Bisantrene Hydrochloride; Bisnafide Dimesylate; Bizelesin; BleomycinSulfate; Brequinar Sodium; Bropirimine; Busulfan; Cactinomycin;Calusterone; Camptothecin; Caracemide; Carbetimer; Carboplatin;Carmustine; Carubicin Hydrochloride; Carzelesin; Cedefingol;Chlorambucil; Cirolemycin; Cisplatin; Cladribine; Combretestatin A-4;Crisnatol Mesylate; Cyclophosphamide; Cytarabine; Dacarbazine; DACA(N-[2-(Dimethyl-amino) ethyl]acridine-4-carboxamide); Dactinomycin;Daunorubicin Hydrochloride; Daunomycin; Decitabine; Dexormaplatin;Dezaguanine; Dezaguanine Mesylate; Diaziquone; Docetaxel; Dolasatins;Doxorubicin; Doxorubicin Hydrochloride; Droloxifene; DroloxifeneCitrate; Dromostanolone Propionate; Duazomycin; Edatrexate; EflomithineHydrochloride; Ellipticine; Elsamitrucin; Enloplatin; Enpromate;Epipropidine; Epirubicin Hydrochloride; Erbulozole; EsorubicinHydrochloride; Estramustine; Estramustine Phosphate Sodium; Etanidazole;Ethiodized Oil I 131; Etoposide; Etoposide Phosphate; Etoprine;Fadrozole Hydrochloride; Fazarabine; Fenretinide; Floxuridine;Fludarabine Phosphate; Fluorouracil; 5-FdUMP; Fluorocitabine;Fosquidone; Fostriecin Sodium; Gemcitabine; Gemcitabine Hydrochloride;Gold Au 198; Homocamptothecin; Hydroxyurea; Idarubicin Hydrochloride;Ifosfamide; Ilmofosine; Interferon Alfa-2a; Interferon Alfa-2b;Interferon Alfa-n1; Interferon Alfa-n3; Interferon Beta-I a; InterferonGamma-I b; Iproplatin; Irinotecan Hydrochloride; Lanreotide Acetate;Letrozole; Leuprolide Acetate; Liarozole Hydrochloride; LometrexolSodium; Lomustine; Losoxantrone Hydrochloride; Masoprocol; Maytansine;Mechlorethamine Hydrochloride; Megestrol Acetate; Melengestrol Acetate;Melphalan; Menogaril; Mercaptopurine; Methotrexate; Methotrexate Sodium;Metoprine; Meturedepa; Mitindomide; Mitocarcin; Mitocromin; Mitogillin;Mitomalcin; Mitomycin; Mitosper; Mitotane; Mitoxantrone Hydrochloride;Mycophenolic Acid; Nocodazole; Nogalamycin; Ormaplatin; Oxisuran;Paclitaxel; Pegaspargase; Peliomycin; Pentamustine; PeploycinSulfate;Perfosfamide; Pipobroman; Piposulfan; Piroxantrone Hydrochloride;Plicamycin; Plomestane; Porfimer Sodium; Porfiromycin; Prednimustine;Procarbazine Hydrochloride; Puromycin; Puromycin Hydrochloride;Pyrazofurin; Rhizoxin; Rhizoxin D; Riboprine; Rogletimide; Safingol;Safingol Hydrochloride; Semustine; Simtrazene; Sparfosate Sodium;Sparsomycin; Spirogermanium Hydrochloride; Spiromustine; Spiroplatin;Streptonigrin; Streptozocin; Strontium Chloride Sr 89; Sulofenur;Talisomycin; Taxane; Taxoid; Tecogalan Sodium; Tegafur; TeloxantroneHydrochloride; Temoporfin; Teniposide; Teroxirone; Testolactone;Thiamiprine; Thioguanine; Thiotepa; Thymitaq; Tiazofurin; Tirapazamine;Tomudex; TOP53; Topotecan Hydrochloride; Toremifene Citrate; TrestoloneAcetate; Triciribine Phosphate; Trimetrexate; Trimetrexate Glucuronate;Triptorelin; Tubulozole Hydrochloride; Uracil Mustard; Uredepa;Vapreotide; Verteporfin; Vinblastine; Vinblastine Sulfate; Vincristine;Vincristine Sulfate; Vindesine; Vindesine Sulfate; Vinepidine Sulfate;Vinglycinate Sulfate; Vinleurosine Sulfate; Vinorelbine Tartrate;Vinrosidine Sulfate; Vinzolidine Sulfate; Vorozole; Zeniplatin;Zinostatin; Zorubicin Hydrochloride; 2-Chlorodeoxyadenosine; 2′Deoxyformycin; 9-aminocamptothecin; raltitrexed;N-propargyl-5,8-dideazafolic acid;2chloro-2′-arabino-fluoro-2′-deoxyadenosine; 2-chloro-2′-deoxyadenosine;anisomycin; trichostatin A; hPRL-G129R; CEP-751; linomide; sulfurmustard; nitrogen mustard (mechlor ethamine); cyclophosphamide;melphalan; chlorambucil; ifosfamide; busulfan; N-methyl-Nnitrosourea(MNU); N,N′-Bis(2-chloroethyl)-N-nitrosourea (BCNU);N-(2-chloroethyl)-N′ cyclohexyl-N-nitrosourea (CCNU);N-(2-chloroethyl)-N′-(trans-4-methylcyclohexyl-N-nitrosourea (MeCCNU);N-(2-chloroethyl)-N′-(diethyl)ethylphosphonate-N-nitrosourea(fotemustine); streptozotocin; diacarbazine (DTIC); mitozolomide;temozolomide; thiotepa; mitomycin C; AZQ; adozelesin; Cisplatin;Carboplatin; Ormaplatin; Oxaliplatin; C1-973; DWA 2114R; JM216; JM335;Bis(platinum); tomudex; azacitidine; cytarabine; gemcitabine;6-Mercaptopurine; 6-Thioguanine; Hypoxanthine; teniposide 9-aminocamptothecin; Topotecan; CPT-11; Doxorubicin; Daunomycin; Epirubicin;darubicin; mitoxantrone; losoxantrone; Dactinomycin (Actinomycin D);amsacrine; pyrazoloacridine; all-trans retinol;14-hydroxy-retro-retinol; all-trans retinoic acid;N-(4-Hydroxyphenyl)retinamide; 13-cis retinoic acid; 3-Methyl TTNEB;9-cis retinoic acid; fludarabine (2-F-ara-AMP); and2-chlorodeoxyadenosine (2-Cda).

Other chemotherapeutic agents include, but are not limited to,20-pi-1,25 dihydroxyvitamin D3; 5-ethynyluracil; abiraterone;aclarubicin; acylfulvene; adecypenol; adozelesin; aldesleukin; ALL-TKantagonists; altretamine; ambamustine; amidox; amifostine;aminolevulinic acid; amrubicin; amsacrine; anagrelide; anastrozole;andrographolide; angiogenesis inhibitors; antagonist D; antagonist G;antarelix; anti-dorsalizing morphogenetic protein-1; antiandrogen;antiestrogen; antineoplaston; antisense oligonucleotides; aphidicolinglycinate; apoptosis gene modulators; apoptosis regulators; apurinicacid; ara-CDP-DL-PTBA; argininedeaminase; asulacrine; atamestane;atrimustine; axinastatin 1; axinastatin 2; axinastatin 3; azasetron;azatoxin; azatyrosine; baccatin III derivatives; balanol; batimastat;BCR/ABL antagonists; benzochlorins; benzoylstaurosporine; beta lactamderivatives; beta-alethine; betaclamycin B; betulinic acid; bFGFinhibitor; bicalutamide; bisantrene; bisaziridinylspermine; bisnafide;bistratene A; bizelesin; breflate; bleomycin A2; bleomycin B2;bropirimine; budotitane; buthionine sulfoximine; calcipotriol;calphostin C; camptothecin derivatives (e.g., 10-hydroxy-camptothecin);canarypox IL-2; capecitabine; carboxamide-amino-triazole;carboxyamidotriazole; CaRest M3; CARN 700; cartilage derived inhibitor;carzelesin; casein kinase inhibitors (ICOS); castanospermine; cecropinB; cetrorelix; chlorins; chloroquinoxaline sulfonamide; cicaprost;cis-porphyrin; cladribine; clomifene analogues; clotrimazole;collismycin A; collismycin B; combretastatin A4; combretastatinanalogue; conagenin; crambescidin 816; crisnatol; cryptophycin 8;cryptophycin A derivatives; curacin A; cyclopentanthraquinones;cycloplatam; cypemycin; cytarabine ocfosfate; cytolytic factor;cytostatin; dacliximab; decitabine; dehydrodidemnin B; 2′deoxycoformycin(DCF); deslorelin; dexifosfamide; dexrazoxane; dexverapamil; diaziquone;didemnin B; didox; diethylnorspermine; dihydro-5-azacytidine;9-dihydrotaxol; dioxamycin; diphenyl spiromustine; discodermolide;docosanol; dolasetron; doxifluridine; droloxifene; dronabinol;duocarmycin SA; ebselen; ecomustine; edelfosine; edrecolomab;eflomithine; elemene; emitefur; epirubicin; epothilones (A, R═H; B,R=Me); epithilones; epristeride; estramustine analogue; estrogenagonists; estrogen antagonists; etanidazole; etoposide; etoposide4′-phosphate (etopofos); exemestane; fadrozole; fazarabine; fenretinide;filgrastim; finasteride; flavopiridol; flezelastine; fluasterone;fludarabine; fluorodaunorunicin hydrochloride; forfenimex; formestane;fostriecin; fotemustine; gadolinium texaphyrin; gallium nitrate;galocitabine; ganirelix; gelatinase inhibitors; gemcitabine; glutathioneinhibitors; hepsulfam; heregulin; hexamethylene bisacetamide;homoharringtonine (HHT); hypericin; ibandronic acid; idarubicin;idoxifene; idramantone; ilmofosine; ilomastat; imidazoacridones;imiquimod; immunostimulant peptides; insulin-like growth factor-1receptor inhibitor; interferon agonists; interferons; interleukins;iobenguane; iododoxorubicin; 4-ipomeanol; irinotecan; iroplact;irsogladine; isobengazole; isohomohalicondrin B; itasetron;jasplakinolide; kahalalide F; lamellarin-N triacetate; lanreotide;leinamycin; lenograstim; lentinan sulfate; leptolstatin; letrozole;leukemia inhibiting factor; leukocyte alpha interferon; leuprolide,estrogen, and progesterone combinations; leuprorelin; levamisole;liarozole; linear polyamine analogue; lipophilic disaccharide peptide;lipophilic platinum compounds; lissoclinamide 7; lobaplatin; lombricine;lometrexol; lonidamine; losoxantrone; lovastatin; loxoribine;lurtotecan; lutetium texaphyrin; lysofylline; lytic peptides;maytansine; mannostatin A; marimastat; masoprocol; maspin; matrilysininhibitors; matrix metalloproteinase inhibitors; menogaril; merbarone;meterelin; methioninase; metoclopramide; MIF inhibitor; ifepristone;miltefosine; mirimostim; mismatched double stranded RNA; mithracin;mitoguazone; mitolactol; mitomycin analogues; mitonafide; mitotoxinfibroblast growth factor-saporin; mitoxantrone; mofarotene;molgramostim; monoclonal antibody, human chorionic gonadotrophin;monophosphoryl lipid A and myobacterium cell wall skeleton combinations;mopidamol; multiple drug resistance gene inhibitor; multiple tumorsuppressor 1-based therapy; mustard anticancer agent; mycaperoxide B;mycobacterial cell wall extract; myriaporone; N-acetyldinaline;N-substituted benzamides; nafarelin; nagrestip; naloxone and pentazocinecombinations; napavin; naphterpin; nartograstim; nedaplatin;nemorubicin; neridronic acid; neutral endopeptidase; nilutamide;nisamycin; nitric oxide modulators; nitroxide antioxidant; nitrullyn;06-benzylguanine; octreotide; okicenone; oligonucleotides; onapristone;ondansetron; ondansetron; oracin; oral cytokine inducer; ormaplatin;osaterone; oxaliplatin; oxaunomycin; paclitaxel analogues; paclitaxelderivatives; palauamine; palmitoylrhizoxin; pamidronic acid;panaxytriol; panomifene; parabactin; pazelliptine; pegaspargase;peldesine; pentosan polysulfate sodium; pentostatin; pentrozole;perflubron; perfosfamide; perillyl alcohol; phenazinomycin;phenylacetate; phosphatase inhibitors; picibanil; pilocarpinehydrochloride; pirarubicin; piritrexim; placetin A; placetin B;plasminogen activator inhibitor; platinum complex; platinum compounds;platinum-triamine complex; podophyllotoxin; porfimer sodium;porfiromycin; propyl bis-acridone; prostaglandin J2; proteasomeinhibitors; protein A-based immune modulator; protein kinase Cinhibitor; protein kinase C inhibitors, microalgal; protein tyrosinephosphatase inhibitors; purine nucleoside phosphorylase inhibitors;purpurins; pyrazoloacridine; pyridoxylated hemoglobin polyoxyethyleneconjugate; raf antagonists; raltitrexed; ramosetron; ras farnesylprotein transferase inhibitors; ras inhibitors; ras-GAP inhibitor;retelliptine demethylated; rhenium Re 186 etidronate; rhizoxin;ribozymes; RII retinamide; rogletimide; rohitukine; romurtide;roquinimex; rubiginone B1; ruboxyl; safingol; saintopin; SarCNU;sarcophytol A; sargramostim; Sd±1 mimetics; semustine; senescencederived inhibitor 1; sense oligonucleotides; signal transductioninhibitors; signal transduction modulators; single chain antigen bindingprotein; sizofuran; sobuzoxane; sodium borocaptate; sodiumphenylacetate; solverol; somatomedin binding protein; sonermin;sparfosic acid; spicamycin D; spiromustine; splenopentin; spongistatin1; squalamine; stem cell inhibitor; stem-cell division inhibitors;stipiamide; stromelysin inhibitors; sulfinosine; superactive vasoactiveintestinal peptide antagonist; suradista; suramin; swainsonine;synthetic glycosaminoglycans; tallimustine; tamoxifen methiodide;tauromustine; tazarotene; tecogalan sodium; tegafur; tellurapyrylium;telomerase inhibitors; temoporfin; temozolomide; teniposide;tetrachlorodecaoxide; tetrazomine; thaliblastine; thalidomide;thiocoraline; thrombopoietin; thrombopoietin mimetic; thymalfasin;thymopoietin receptor agonist; thymotrinan; thyroid stimulating hormone;tin ethyl etiopurpurin; tirapazamine; titanocene dichloride; topotecan;topsentin; toremifene; totipotent stem cell factor; translationinhibitors; tretinoin; triacetyluridine; triciribine; trimetrexate;triptorelin; tropisetron; turosteride; tyrosine kinase inhibitors;tyrphostins; UBC inhibitors; ubenimex; urogenital sinus-derived growthinhibitory factor; urokinase receptor antagonists; vapreotide; variolinB; vector system, erythrocyte gene therapy; velaresol; veramine;verdins; verteporfin; vinorelbine; vinxaltine; vitaxin; vorozole;zanoterone; zeniplatin; zilascorb; and zinostatin stimalamer.

To “inhibit growth” as used herein means causing a reduction in cellgrowth in vivo or in vitro by, e.g., 10%, 20%, 30%, 40%, 50%, 60%, 70%,80%, 90%, 95%, or 99% or more, as evident by a reduction in the size ornumber of cells exposed to a treatment (e.g., exposure to a compound),relative to the size or number of cells in the absence of the treatment.Growth inhibition can be the result of a treatment that inducesapoptosis in a cell, induces necrosis in a cell, slows cell cycleprogression, disrupts cellular metabolism, induces cell lysis, orinduces some other mechanism that reduces the size or number of cells.

“Biomarker gene” as used herein means a gene in a cell (e.g., a cancercell) the expression of which, as measured by, e.g., detecting the levelof one or more biomarkers produced from the gene, correlates tosensitivity or resistance of the cell, tissue, organism, or patient(e.g., a human) to a treatment (e.g., chemotherapy, radiation therapy,or surgery).

“Microarray” as used herein means a device employed by any method thatquantifies one or more subject oligonucleotides, e.g., DNA or RNA, oranalogues thereof, at a time. One exemplary class of microarraysconsists of DNA probes attached to a glass or quartz surface. Manymicroarrays, e.g., those made by Affymetrix, use several probes fordetermining the expression of a single gene. The DNA microarray cancontain oligonucleotide probes that may be, e.g., full-length cDNAscomplementary to an RNA or cDNA fragments that hybridize to part of anRNA. Exemplary RNAs include mRNA, miRNA, and miRNA precursors. Exemplarymicroarrays also include a “nucleic acid microarray” having asubstrate-bound plurality of nucleic acids, hybridization to each of theplurality of bound nucleic acids being separately detectable. Thesubstrate can be solid or porous, planar or non-planar, unitary ordistributed. Exemplary nucleic acid microarrays include all of thedevices so called in Schena (ed.), DNA Microarrays: A Practical Approach(Practical Approach Series), Oxford University Press (1999); NatureGenet. 21(1)(suppl.):1-60 (1999); and Schena (ed.), Microarray Biochip:Tools and Technology, Eaton Publishing Company/BioTechniques BooksDivision (2000). Additionally, exemplary nucleic acid microarrays caninclude a substrate-bound plurality of nucleic acids in which theplurality of nucleic acids is disposed on a plurality of beads, ratherthan on a unitary planar substrate, as is described, inter alia, inBrenner et al., Proc. Natl. Acad. Sci. USA 97(4):1665-1670 (2000).Examples of nucleic acid microarrays may be found in U.S. Pat. Nos.6,391,623, 6,383,754, 6,383,749, 6,380,377, 6,379,897, 6,376,191,6,372,431, 6,351,712 6,344,316, 6,316,193, 6,312,906, 6,309,828,6,309,824, 6,306,643, 6,300,063, 6,287,850, 6,284,497, 6,284,465,6,280,954, 6,262,216, 6,251,601, 6,245,518, 6,263,287, 6,251,601,6,238,866, 6,228,575, 6,214,587, 6,203,989, 6,171,797, 6,103,474,6,083,726, 6,054,274, 6,040,138, 6,083,726, 6,004,755, 6,001,309,5,958,342, 5,952,180, 5,936,731, 5,843,655, 5,814,454, 5,837,196,5,436,327, 5,412,087, and 5,405,783, herein incorporated by reference.

Exemplary microarrays can also include “peptide microarrays” or “proteinmicroarrays” having a substrate-bound plurality of polypeptides, thebinding of a oligonucleotide, a peptide, or a protein to the pluralityof bound polypeptides being separately detectable. Alternatively, thepeptide microarray, can have a plurality of binders, including, but notlimited to, monoclonal antibodies, polyclonal antibodies, phage displaybinders, yeast 2 hybrid binders, aptamers, that can specifically detectthe binding of specific oligonucleotides, peptides, or proteins.Examples of peptide arrays may be found in International PatentPublication Nos. WO 02/31463, WO 02/25288, WO 01/94946, WO 01/88162, WO01/68671, WO 01/57259, WO 00/61806, WO 00/54046, WO 00/47774, WO99/40434, WO 99/39210, and WO 97/42507, and in U.S. Pat. Nos. 6,268,210,5,766,960, and 5,143,854, herein incorporated by reference.

“Gene expression” as used herein means the level of expression of abiomarker gene (e.g., the level of a transcription product, such as anmRNA, tRNA, or microRNA, or its complement (e.g., a cDNA complement ofthe transcription product), or a translation product, such as apolypeptide or metabolite thereof) in a cell, tissue, organism, orpatient (e.g., a human). Gene expression can be measured by detectingthe presence, quantity, or activity of a DNA, RNA, or polypeptide, ormodifications thereof (e.g., splicing, phosphorylation, and acetylation)associated with a given gene.

“NCI60” as used herein means a panel of 60 cancer cell lines from lung,colon, breast, ovarian, leukemia, renal, melanoma, prostate, and braincancers including the following cancer cell lines: NSCLC_NCIH23,NSCLC_NCIH522, NSCLC_A549ATCC, NSCLC_EKVX, NSCLC_NCIH226,NSCLC_NCIH332M, NSCLC_H460, NSCLC_HOP62, NSCLC_HOP92, COLON_HT29,COLON_HCC-2998, COLON_HCT116, COLON_SW620, COLON_COLO205, COLON_HCT15,COLON_KM12, BREAST_MCF7, BREAST_MCF7ADRr, BREAST_MDAMB231,BREAST_HS578T, BREAST_MDAMB435, BREAST_MDN, BREAST_BT549, BREAST_T47D,OVAR_OVCAR3, OVAR_OVCAR4, OVAR_OVCAR5, OVAR_OVCAR8, OVAR_IGROV1,OVAR_SKOV3, LEUK_CCRFCEM, LEUK_K562, LEUK_MOLT4, LEUK_HL60,LEUK_RPMI8266, LEUK_SR, RENAL_UO31, RENAL_SN12C, RENAL_A498,RENAL_CAKI1, RENAL_RXF393, RENAL_(—)7860, RENAL_ACHN, RENAL_TK10,MELAN_LOXIMVI, MELAN_MALME3M, MELAN_SKMEL2, MELAN_SKMEL5, MELAN_SKMEL28,MELAN_M14, MELAN_UACC62, MELAN_UACC257, PROSTATE_PC3, PROSTATE_DU145,CNS_SNB19, CNS_SNB75, CNS_U251, CNS_SF268, CNS_SF295, and CNS_SF539.

“Treatment” or “medical treatment” means administering to a patient(e.g., a human) or living organism or exposing to a cell or tumor acompound (e.g., a drug, a protein, an antibody, an oligonucleotide, achemotherapeutic agent, and a radioactive agent) or some other form ofmedical intervention used to treat or prevent cancer or the symptoms ofcancer (e.g., cryotherapy and radiation therapy). Radiation therapyincludes the administration to a patient of radiation generated fromsources such as particle accelerators and related medical devices thatemit X-radiation, gamma radiation, or electron (Beta radiation) beams. Atreatment may further include surgery, e.g., to remove a tumor from apatient or living organism.

Other features and advantages of the invention will be apparent from thefollowing description, drawings, and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an illustration of the method of identifying biomarkersand predicting patient sensitivity to a medical treatment. The methodhas an in vitro component where the growth inhibition of a compound ormedical treatment is measured on cell lines (6 of the 60 cell linestested are shown). The gene expression is measured on the same celllines without compound treatment. Those genes that have a correlationabove a certain cutoff (e.g., a preferred cutoff of 0.3, in which acorrelation coefficient equal to or greater than the cutoff of 0.3 isdeemed statistically significant by, e.g., cross-validation) to thegrowth inhibition are termed marker genes and the expression of thosegenes in vivo, e.g., may predict the sensitivity or resistance of apatient's cancer to a compound or other medical treatment. The in vivocomponent is applied to a patient to determine whether or not thetreatment will be effective in treating disease in the patient. Here,the gene expression in cells of a sample of the suspected disease tissue(e.g., a tumor) in the patient is measured before or after treatment.The activity of the marker genes in the sample is compared to areference population of patients known to be sensitive or resistant tothe treatment. The expression of marker genes in the cells of thepatient known to be expressed in the cells of reference patientssensitive to the treatment indicates that the patient to be treated issensitive to the treatment and vice versa. Based on this comparison thepatient is predicted to be sensitive or resistant to treatment with thecompound.

FIG. 2 depicts the treatment sensitivity predictions for a 5-year-oldAmerican boy with a brain tumor. The subject had surgery to remove thetumor and, based on the analysis of gene expression in cells from asample of the tumor, the subject was predicted to be chemosensitive toten chemotherapy drugs. The subject received Vincristine and Cisplatinand survived.

FIG. 3 depicts the treatment sensitivity predictions for a 7-month-oldAmerican girl with a brain tumor. The subject had surgery to remove thetumor, and based on the analysis of gene expression in cells from asample of the tumor, the subject was predicted to be chemoresistant totwelve chemotheraphydrugs. The subject received Vincristine andCisplatin, but passed away 9 months later.

FIG. 4 depicts the survival rate of 60 brain cancer patients dividedinto a group predicted to be chemosensitive to Cisplatin and a grouppredicted to be chemoresistant to Cisplatin. All patients receivedCisplatin after surgery.

FIG. 5 depicts the survival rate of 56 lymphoma patients divided into agroup predicted to be chemosensitive to Vincristine and Adriamycin and agroup predicted to be chemoresistant. All patients received Vincristineand Adriamycin.

FIG. 6 depicts the survival rate of 19 lung cancer patients divided intoa group predicted to be chemosensitive to Cisplatin and a grouppredicted to be chemoresistant. All patients received Cisplatin.

FIG. 7 depicts the survival rate of 14 diffuse large-B-cell lymphoma(DLBCL) patients divided into a group predicted to be chemosensitive tothe drug combination R-CHOP and a group predicted to be chemoresistant.All patients were treated with R-CHOP.

FIG. 8 depicts the predictions of sensitivity or resistance to treatmentof a patient diagnosed with DLBCL. Various drug combinations andradiation therapy are considered. The drug combinations (indicated byabbreviations) are those commonly used to treat DLBCL.

FIG. 9 depicts the survival rate of 60 brain cancer patients dividedinto a group predicted to be sensitive to radiation treatment and agroup predicted to be resistant. All patients were treated withradiation.

FIG. 10 depicts the survival rate of 60 brain cancer patients dividedinto a group predicted to be sensitive to radiation treatment and agroup predicted to be resistant. All patients were treated withradiation. Gene biomarkers used in predicting radiation sensitivity orresistance were obtained using the correlation of the median geneexpression measurement to cancer cell growth as opposed to the median ofthe correlations as employed in FIG. 9.

FIG. 11 depicts the predicted sensitivity of cancer patients tosunitinib. The cancer patients are grouped according to cancer type ororigin and cancer types with predicted high sensitivity are labeled.

DETAILED DESCRIPTION

The invention features methods for identifying biomarkers of treatmentsensitivity, e.g., chemosensitivity to compounds, or resistance, devicesthat include the biomarkers, kits that include the devices, and methodsfor predicting treatment efficacy in a patient (e.g., a human diagnosedwith cancer). The kits of the invention include microarrays havingoligonucleotide probes that are biomarkers of sensitivity or resistanceto treatment (e.g., treatment with a chemotherapeutic agent) thathybridize to nucleic acids derived from or obtained from a subject andinstructions for using the device to predict the sensitivity orresistance of the subject to the treatment. The invention also featuresmethods of using the microarrays to determine whether a subject, e.g., acancer patient, will be sensitive or resistant to treatment with, e.g.,a chemotherapy agent. Also featured are methods of identifyingbiomarkers of sensitivity or resistance to a medical treatment based onthe correlation of gene or microRNA expression to treatment efficacy,e.g., the growth inhibition of cancer cells. Gene or microRNA biomarkersthat identify subjects as sensitive or resistant to a treatment can alsobe identified within patient populations already thought to be sensitiveor resistant to that treatment. Thus, the methods, devices, and kits ofthe invention can be used to identify patient subpopulations that areresponsive to a treatment thought to be ineffective for treating disease(e.g., cancer) in the general population. More generally, cancer patientsensitivity to a compound or other medical treatment can be predictedusing biomarker expression regardless of prior knowledge about patientresponsiveness to treatment. The method according to the presentinvention can be implemented using software that is run on an apparatus(e.g., a computer) for measuring biomarker expression in connection witha microarray. The microarray (e.g., a DNA microarray), included in a kitfor processing a tumor sample from a patient, and the apparatus forreading the microarray and turning the result into a chemosensitivityprofile for the patient may be used to implement the methods of theinvention.

Microarrays Containing Oligonucleotide Probes

The microarrays of the invention include one or more oligonucleotideprobes that have nucleotide sequences that are substantially identicalto or substantially complementary to, e.g., at least 5, 8, 12, 20, 30,40, 60, 80, 100, 150, or 200 consecutive nucleotides (or nucleotideanalogues) of the biomarker genes or biomarker gene products (e.g.,transcription or translation gene products, such as microRNAs) listedbelow. The oligonucleotide probes may be, e.g., 5-20, 25, 5-50, 50-100,or over 100 nucleotides long. The oligonucleotide probes may bedeoxyribonucleic acids (DNA) or ribonucleic acids (RNA). Consecutivenucleotides within the oligonucleotide probes (e.g., 5-20, 25, 5-50,50-100, or over 100 consecutive nucleotides), which are used asbiomarkers of chemosensitivity, may also appear as consecutivenucleotides in one or more of the genes described herein beginning at ornear, e.g., the first, tenth, twentieth, thirtieth, fortieth, fiftieth,sixtieth, seventieth, eightieth, ninetieth, hundredth, hundred-fiftieth,two-hundredth, five-hundredth, or one-thousandth nucleotide of the genesor microRNAs listed in Tables 1-136 below. Column List_(—)2006 of Tables1-21 indicates the preferred biomarker genes for the compound lists.Column List_Preferred of Tables 1-21 indicates the most preferredbiomarker genes. Column List_(—)2005 of Tables 1-21 indicates additionalbiomarkers employed in Examples 1-8. Column Correlation of Tables 1-21indicates the correlation coefficient of the biomarker gene expressionto cancer cell growth inhibition. Tables 80-136 indicate microRNAbiomarkers that can be used to determine a patient's (e.g., a human's)sensitivity to a treatment. The following combinations of biomarkershave been used to detect a patient's sensitivity to the indicatedtreatment:

a) One or more of the gene sequences SFRS3, CCT5, RPL39, SLC25A5, UBE2S,EEF1A1, RPLP2, RPL24, RPS23, RPL39, RPL18, NCL, RPL9, RPL10A, RPS10,E1F3S2, SHFM1, RPS28, REA, RPL36A, GAPD, HNRPA1, RPS11, HNRPA1, LDHB,RPL3, RPL11, MRPL12, RPL18A, COX7B, and RPS7, preferably gene sequencesUBB, RPS4X, S100A4, NDUFS6, B2M, C14orf139, MANIA 1, SLC25A5, RPL10,RPL12, E1F5A, RPL36A, SUI1, BLMH, CTBP1, TBCA, MDH2, and DXS9879E, andmost preferably gene sequences RPS4X, S100A4, NDUFS6, C14orf139,SLC25A5, RPL10, RPL12, EIF5A, RPL36A, BLMH, CTBP1, TBCA, MDH2, andDXS9879E, whose expression indicates chemosensitivity to Vincristine.b) One or more of the gene sequences B2M, ARHGDIB, FTL, NCL, MSN, SNRPF,XPO1, LDHB, SNRPF, GAPD, PTPN7, ARHGDIB, RPS27, IFI16, C5orf13, andHCLS1, preferably gene sequences C1QR1, HCLS1, CD53, SLA, PTPN7,PTPRCAP, ZNFN1A1, CENTB1, PTPRC, IFI16, ARHGEF6, SEC31L2, CD3Z, GZMB,CD3D, MAP4K1, GPR65, PRF1, ARHGAP15, TM6SF1, and TCF4, and mostpreferably gene sequences C1QR1, SLA, PTPN7, ZNFN1A1, CENTB1, IFI16,ARHGEF6, SEC31L2, CD3Z, GZMB, CD3D, MAP4K1, GPR65, PRF1, ARHGAP15,TM6SF1, and TCF4, whose expression indicates chemosensitivity toCisplatin.c) One or more of the gene sequences PRPS1, DDOST, B2M, SPARC, LGALS1,CBFB, SNRPB2, MCAM, MCAM, E1F2S2, HPRT1, SRM, FKBP1A, GYPC, UROD, MSN,HNRPA1, SND1, COPA, MAPRE1, E1F3S2, ATP1B3, EMP3, ECM1, ATOX1, NARS,PGK1, OK/SW-c1.56, FN1, EEF1A1, GNAI2, PRPS1, RPL7, PSMB9, GPNMB,PPP1R11, MIA, RAB7, VIM, and SMS, preferably gene sequences MSN, SPARC,VIM, SRM, SCARB1, SIAT1, CUGBP2, GAS7, ICAM1, WASPIP, ITM2A,PALM2-AKAP2, ANPEP, PTPNS1, MPP1, LNK, FCGR2A, EMP3, RUNX3, EVI2A,BTN3A3, LCP2, BCHE, LY96, LCP1, IFI16, MCAM, MEF2C, SLC1A4, BTN3A2, FYN,FN1, C1orf38, CHS1, CAPN3, FCGR2C, TNIK, AMPD2, SEPT6, RAFTLIN, SLC43A3,RAC2, LPXN, CKIP-1, FLJ10539, FLJ35036, DOCK10, TRPV2, IFRG28, LEF1, andADAMTS1, and most preferably gene sequences SRM, SCARB1, SIAT1, CUGBP2,ICAM1, WASPIP, ITM2A, PALM2-AKAP2, PTPNS1, MPP1, LNK, FCGR2A, RUNX3,EVI2A, BTN3A3, LCP2, BCHE, LY96, LCP1, IFI16, MCAM, MEF2C, SLC1A4, FYN,C1orf38, CHS1, FCGR2C, TNIK, AMPD2, SEPT6, RAFTLIN, SLC43A3, RAC2, LPXN,CKIP-1, FLJ10539, FLJ35036, DOCK10, TRPV2, IFRG28, LEF1, and ADAMTS1,whose expression indicates chemosensitivity to Azaguanine.d) One or more of the gene sequences B2M, MYC, CD99, RPS24, PPIF, PBEF1,and ANP32B, preferably gene sequences CD99, INSIG1, LAPTM5, PRG1, MUF1,HCLS1, CD53, SLA, SSBP2, GNB5, MFNG, GMFG, PSMB9, EVI2A, PTPN7, PTGER4,CXorf9, PTPRCAP, ZNFN1A1, CENTB1, PTPRC, NAP1L1, HLA-DRA, IFI16, CORO1A,ARHGEF6, PSCDBP, SELPLG, LAT, SEC31L2, CD3Z, SH2D1A, GZMB, SCN3A, ITK,RAFTLIN, DOCK2, CD3D, RAC2, ZAP70, GPR65, PRF1, ARHGAP15, NOTCH1, andUBASH3A, and most preferably gene sequences CD99, INSIG1, PRG1, MUF1,SLA, SSBP2, GNB5, MFNG, PSMB9, EVI2A, PTPN7, PTGER4, CXorf9, ZNFN1A1,CENTB1, NAP1L1, HLA-DRA, IFI16, ARHGEF6, PSCDBP, SELPLG, LAT, SEC31L2,CD3Z, SH2D1A, GZMB, SCN3A, RAFTLIN, DOCK2, CD3D, RAC2, ZAP70, GPR65,PRF1, ARHGAP15, NOTCH1, and UBASH3A, whose expression indicateschemosensitivity to Etoposide.e) One or more of the gene sequences KIAA0220, B2M, TOP2A, CD99, SNRPE,RPS27, HNRPA1, CBX3, ANP32B, HNRPA1, DDX5, PPIA, SNRPF, and USP7,preferably gene sequences CD99, LAPTM5, ALDOC, HCLS1, CD53, SLA, SSBP2,IL2RG, GMFG, CXorf9, RHOH, PTPRCAP, ZNFN1A1, CENTB1, TCF7, CD1C, MAP4K1,CD1B, CD3G, PTPRC, CCR9, CORO1A, CXCR4, ARHGEF6, HEM1, SELPLG, LAT,SEC31L2, CD3Z, SH2D1A, CD1A, LAIR1, ITK, TRB@, CD3D, WBSCR20C, ZAP70,IFI44, GPR65, AIF1, ARHGAP15, NARF, and PACAP, and most preferably genesequences CD99, ALDOC, SLA, SSBP2, IL2RG, CXorf9, RHOH, ZNFN1A1, CENTB1,CD1C, MAP4K1, CD3G, CCR9, CXCR4, ARHGEF6, SELPLG, LAT, SEC31L2, CD3Z,SH2D1A, CD 1A, LAIR1, TRB@, CD3D, WBSCR20C, ZAP70, IFI44, GPR65, AIF1,ARHGAP15, NARF, and PACAP, whose expression indicates chemosensitivityto Adriamycin.f) One or more of the gene sequences RPLP2, LAMR1, RPS25, EIF5A, TUFM,HNRPA1, RPS9, MYB, LAMR1, ANP32B, HNRPA1, HNRPA1, EIF4B, HMGB2, RPS15A,and RPS7, preferably gene sequences RPL12, RPL32, RPLP2, MYB, ZNFN1A1,SCAP1, STAT4, SP140, AMPD3, TNFAIP8, DDX18, TAF5, FBL, RPS2, PTPRC,DOCK2, GPR65, HOXA9, FLJ12270, and HNRPD, and most preferably genesequences RPL12, RPLP2, MYB, ZNFN1A1, SCAP1, STAT4, SP140, AMPD3,TNFAIP8, DDX18, TAF5, RPS2, DOCK2, GPR65, HOXA9, FLJ12270, and HNRPD,whose expression indicates chemosensitivity to Aclarubicin.g) One or more of the gene sequences ARHGEF6, B2M, TOP2A, TOP2A, ELA2B,PTMA, LMNB1, TNFRSF1A, NAP1L1, B2M, HNRPA1, RPL9, C5orf13, NCOR2,ANP32B, OK/SW-c1.56, TUBA3, HMGN2, PRPS1, DDX5, PRG1, PPIA, G6PD, PSMB9,SNRPF, and MAP1B, preferably gene sequences PGAM1, DPYSL3, INSIG1, GJA1,BNIP3, PRG1, G6PD, BASP1, PLOD2, LOXL2, SSBP2, C1orf29, TOX, STC1,TNFRSF1A, NCOR2, NAP1L1, LOC94105, COL6A2, ARHGEF6, GATA3, TFPI, LAT,CD3Z, AF1Q, MAP1B, PTPRC, PRKCA, TRIM22, CD3D, BCAT1, IFI44, CCL2,RAB31, CUTC, NAP1L2, NME7, FLJ21159, and COL5A2, and most preferablygene sequences PGAM1, DPYSL3, INSIG1, GJA1, BNIP3, PRG1, G6PD, PLOD2,LOXL2, SSBP2, C1orf29, TOX, STC1, TNFRSF1A, NCOR2, NAP1L1, LOC94105,ARHGEF6, GATA3, TFPI, LAT, CD3Z, AF1Q, MAP1B, TRIM22, CD3D, BCAT1,IFI44, CUTC, NAP1L2, NME7, FLJ21159, and COL5A2, whose expressionindicates chemosensitivity to Mitoxantrone.h) One or more of the gene sequences GAPD, GAPD, GAPD, TOP2A, SUI1,TOP2A, FTL, HNRPC, TNFRSF1A, SHC1, CCT7, P4HB, CTSL, DDX5, G6PD, andSNRPF, preferably gene sequences STC1, GPR65, DOCK10, COL5A2, FAM46A,and LOC54103, and most preferably gene sequences STC1, GPR65, DOCK10,COL5A2, FAM46A, and LOC54103, whose expression indicateschemosensitivity to Mitomycin.i) One or more of the gene sequences RPS23, SFRS3, KIAA0114, RPL39,SFRS3, LOC51035, RPS6, EXOSC2, RPL35, IFRD2, SMN2, EEF1A1, RPS3, RPS18,and RPS7, preferably gene sequences RPL10, RPS4X, NUDC, RALY, DKC1,DKFZP564C186, PRP19, RAB9P40, HSA9761, GMDS, CEP1, IL13RA2, MAGEB2,HMGN2, ALMS1, GPR65, FLJ10774, NOL8, DAZAP1, SLC25A15, PAF53, DXS9879E,PITPNC1, SPANXC, and KIAA1393, and most preferably RPL10, RPS4X, NUDC,DKC1, DKFZP564C186, PRP19, RAB9P40, HSA9761, GMDS, CEP1, IL13RA2,MAGEB2, HMGN2, ALMS1, GPR65, FLJ10774, NOL8, DAZAP1, SLC25A15, PAF53,DXS9879E, PITPNC1, SPANXC, and KIAA1393, whose expression indicateschemosensitivity to Paclitaxel.j) One or more of the gene sequences CSDA, LAMR1, and TUBA3, preferablygene sequences PFN1, PGAM1, K-ALPHA-1, CSDA, UCHL1, PWP1, PALM2-AKAP2,TNFRSF1A, ATP5G2, AF1Q, NME4, and FHOD1, and most preferably genesequences PFN1, PGAM1, K-ALPHA-1, CSDA, UCHL1, PWP1, PALM2-AKAP2,TNFRSF1A, ATP5G2, AF1Q, NME4, and FHOD1, whose expression indicateschemosensitivity to Gemcitabine.k) One or more of the gene sequences RPS23, SFRS3, KIAA0114, SFRS3,RPS6, DDX39, and RPS7, preferably gene sequences ANP32B, GTF3A, RRM2,TRIM14, SKP2, TRIP13, RFC3, CASP7, TXN, MCM5, PTGES2, OBFC1, EPB41L4B,and CALML4, and most preferably gene sequences ANP32B, GTF3A, RRM2,TRIM14, SKP2, TRIP13, RFC3, CASP7, TXN, MCM5, PTGES2, OBFC1, EPB41L4B,and CALML4, whose expression indicates chemosensitivity to Taxotere.l) One or more of the gene sequences IL2RG, H1FX, RDBP, ZAP70, CXCR4,TM4SF2, ARHGDIB, CDA, CD3E, STMN1, GNA15, AXL, CCND3, SATB1, EIF5A, LCK,NKX2-5, LAPTM5, IQGAP2, FLII, EIF3S5, TRB, CD3D, HOXB2, GATA3, HMGB2,PSMB9, ATP5G2, CORO1A, ARHGDIB, DRAP1, PTPRCAP, RHOH, and ATP2A3,preferably gene sequences IFITM2, UBE2L6, LAPTM5, USP4, ITM2A, ITGB2,ANPEP, CD53, IL2RG, CD37, GPRASP1, PTPN7, CXorf9, RHOH, GIT2, ADORA2A,ZNFN1A1, GNA15, CEP1, TNFRSF7, MAP4K1, CCR7, CD3G, PTPRC, ATP2A3, UCP2,CORO1A, GATA3, CDKN2A, HEM1, TARP, LAIR1, SH2D1A, FLII, SEPT6, HA-1,CREB3L1, ERCC2, CD3D, LST1, AIF1, ADA, DATF1, ARHGAP15, PLAC8, CECR1,LOC81558, and EHD2, and most preferably gene sequences IFITM2, UBE2L6,USP4, ITM2A, IL2RG, GPRASP1, PTPN7, CXorf9, RHOH, GIT2, ZNFN1A1, CEP1,TNFRSF7, MAP4K1, CCR7, CD3G, ATP2A3, UCP2, GATA3, CDKN2A, TARP, LAIR1,SH2D1A, SEPT6, HA-1, ERCC2, CD3D, LST1, AIF1, ADA, DATF1, ARHGAP15,PLAC8, CECR1, LOC81558, and EHD2, whose expression indicateschemosensitivity to Dexamethasone.m) One or more of the gene sequences TM4SF2, ARHGDIB, ADA, H2AFZ,NAP1L1, CCND3, FABP5, LAMR1, REA, MCM5, SNRPF, and USP7, preferably genesequences ITM2A, RHOH, PRIM1, CENTB1, GNA15, NAP1L1, ATP5G2, GATA3,PRKCQ, SH2D1A, SEPT6, PTPRC, NME4, RPL13, CD3D, CD1E, ADA, and FHOD1,and most preferably gene sequences ITM2A, RHOH, PRIM1, CENTB1, NAP1L1,ATP5G2, GATA3, PRKCQ, SH2D1A, SEPT6, NME4, CD3D, CD1E, ADA, and FHOD1,whose expression indicates chemosensitivity to Ara-C.n) One or more of the gene sequences LGALS9, CD7, IL2RG, PTPN7, ARHGEF6,CENTB1, SEPT6, SLA, LCP1, IFITM1, ZAP70, CXCR4, TM4SF2, ZNF91, ARHGDIB,TFDP2, ADA, CD99, CD3E, CD1C, STMN1, CD53, CD7, GNA15, CCND3, MAZ,SATB1, ZNF22, AES, AIF1, MYB, LCK, C5orf13, NKX2-5, ZNFN1A1, STAT5A,CHI3L2, LAPTM5, MAP4K1, DDX11, GPSM3, TRB, CD3D, CD3G, PRKCB1, CD1E,HCLS1, GATA3, TCF7, RHOG, CDW52, HMGB2, DGKA, ITGB2, PSMB9, IDH2, AES,MCM5, NUCB2, CORO1A, ARHGDIB, PTPRCAP, CD47, RHOH, LGALS9, and ATP2A3,preferably gene sequences CD99, SRRM1, ARHGDIB, LAPTM5, VWF, ITM2A,ITGB2, LGALS9, INPP5D, SATB1, CD53, TFDP2, SLA, IL2RG, MFNG, CD37, GMFG,SELL, CDW52, LRMP, ICAM2, RIMS3, PTPN7, ARHGAP25, LCK, CXorf9, RHOH,PTPRCAP, GIT2, ZNFN1A1, CENTB1, LCP2, SPI1, GNA15, GZMA, CEP1, BLM,CD8A, SCAP1, CD2, CD1C, TNFRSF7, VAV1, MAP4K1, CCR7, C6orf32, ALOX15B,BRDT, CD3G, PTPRC, LTB, ATP2A3, NVL, RASGRP2, LCP1, CORO1A, CXCR4,PRKD2, GATA3, TRA@, PRKCB1, HEM1, KIAA0922, TARP, SEC31L2, PRKCQ,SH2D1A, CHRNA3, CD1A, LST1, LAIR1, CACNA1G, TRB@, SEPT6, HA-1, DOCK2,CD3D, TRD@, T3JAM, FNBP1, CD6, AIF1, FOLH1, CD1E, LY9, UGT2B17, ADA,CDKL5, TRIM, EVL, DATF1, RGC32, PRKCH, ARHGAP15, NOTCH1, BIN2, SEMA4G,DPEP2, CECR1, BCL11B, STAG3, GALNT6, UBASH3A, PHEMX, FLJ13373, LEF1,IL21R, MGC17330, AKAP13, ZNF335, and GIMAP5, and most preferably genesequences CD99, ARHGDIB, VWF, ITM2A, LGALS9, INPP5D, SATB1, TFDP2, SLA,IL2RG, MENG, SELL, CDW52, LRMP, ICAM2, RIMS3, PTPN7, ARHGAP25, LCK,CXorf9, RHOH, GIT2, ZNFN1A1, CENTB1, LCP2, SPI1, GZMA, CEP1, CD8A,SCAP1, CD2, CD1C, TNFRSF7, VAV1, MAP4K1, CCR7, C6orf32, ALOX15B, BRDT,CD3G, LTB, ATP2A3, NVL, RASGRP2, LCP1, CXCR4, PRKD2, GATA3, TRA@,KIAA0922, TARP, SEC31L2, PRKCQ, SH2D1A, CHRNA3, CD1A, LST1, LAIR1,CACNA1G, TRB@, SEPT6, HA-1, DOCK2, CD3D, TRD@, T3JAM, FNBP1, CD6, AIF1,FOLH1, CD1E, LY9, ADA, CDKL5, TRIM, EVL, DATF1, RGC32, PRKCH, ARHGAP15,NOTCH1, BIN2, SEMA4G, DPEP2, CECR1, BCL11B, STAG3, GALNT6, UBASH3A,PHEMX, FLJ13373, LEF1, IL21R, MGC17330, AKAP13, ZNF335, and GIMAP5,whose expression indicates chemosensitivity to Methylprednisolone.o) One or more of the gene sequences RPLP2, RPL4, HMGA1, RPL27, IMPDH2,LAMR1, PTMA, ATP5B, NPM1, NCL, RPS25, RPL9, TRAP1, RPL21, LAMR1, REA,HNRPA1, LDHB, RPS2, NME1, PAICS, EEF1B2, RPS15A, RPL19, RPL6, ATP5G2,SNRPF, SNRPG, and RPS7, preferably gene sequences PRPF8, RPL18, RNPS1,RPL32, EEF1G, GOT2, RPL13A, PTMA, RPS15, RPLP2, CSDA, KHDRBS1, SNRPA,IMPDH2, RPS19, NUP88, ATP5D, PCBP2, ZNF593, HSU79274, PRIM1, PFDN5,OXA1L, H3F3A, ATIC, RPL13, CIAPIN1, FBL, RPS2, PCCB, RBMX, SHMT2, RPLP0,HNRPA1, STOML2, RPS9, SKB1, GLTSCR2, CCNB1IP1, MRPS2, FLJ20859, andFLJ12270, and most preferably gene sequences PRPF8, RPL18, GOT2, RPL13A,RPS15, RPLP2, CSDA, KHDRBS1, SNRPA, IMPDH2, RPS19, NUP88, ATP5D, PCBP2,ZNF593, HSU79274, PRIM1, PFDN5, OXA1L, H3F3A, ATIC, CIAPIN1, RPS2, PCCB,SHMT2, RPLP0, HNRPA1, STOML2, SKB1, GLTSCR2, CCNB1IP1, MRPS2, FLJ20859,and FLJ12270, whose expression indicates chemosensitivity toMethotrexate.p) One or more of the gene sequences ACTB, COL5A1, MT1E, CSDA, COL4A2,MMP2, COL1A1, TNFRSF1A, CFHL1, TGFBI, FSCN1, NNMT, PLAUR, CSPG2, NFIL3,C5orf13, NCOR2, TUBB4, MYLK, TUBA3, PLAU, COL4A2, COL6A2, COL6A3,IFITM2, PSMB9, CSDA, and COL1A1, preferably gene sequences MSN, PFN1,HK1, ACTR2, MCL1, ZYX, RAP 1B, GNB2, EPAS1, PGAM1, CKAP4, DUSP1, MYL9,K-ALPHA-1, LGALS1, CSDA, AKR1B1, IFITM2, ITGA5, VIM, DPYSL3, JUNB,ITGA3, NFKBIA, LAMB1, FHL1, INSIG1, TIMP1, GJA1, PSME2, PRG1, EXT1,DKFZP434J154, OPTN, M6PRBP1, MVP, VASP, ARL7, NNMT, TAP1, COL1A1, BASP1,PLOD2, ATF3, PALM2-AKAP2, IL8, ANPEP, LOXL2, TGFB1, IL4R, DGKA, STC2,SEC61G, NFIL3, RGS3, NK4, F2R, TPM2, PSMB9, LOX, STC1, CSPG2, PTGER4,IL6, SMAD3, PLAU, WNT5A, BDNF, TNFRSF1A, FLNC, DKFZP564K0822, FLOT1,PTRF, HLA-B, COL6A2, MGC4083, TNFRSF10B, PLAGL1, PNMA2, TFPI, LAT, GZMB,CYR61, PLAUR, FSCN1, ERP70, AF1Q, UBC, FGFR1, HIC, BAX, COL4A2, COL6A1,IFITM3, MAP1B, FLJ46603, RAFTLIN, RRAS, FTL, KIAA0877, MT1E, CDC10,DOCK2, TRIM22, RIS1, BCAT1, PRF1, DBN1, MT1K, TMSB10, RAB31, FLJ10350,C1orf24, NME7, TMEM22, TPK1, COL5A2, ELK3, CYLD, ADAMTS1, EHD2, andACTB, and most preferably gene sequences PFN1, HK1, MCL1, ZYX, RAP1B,GNB2, EPAS1, PGAM1, CKAP4, DUSP1, MYL9, K-ALPHA-1, LGALS1, CSDA, IFITM2,ITGA5, DPYSL3, JUNB, NFKBIA, LAMB1, FHL1, INSIG1, TIMP1, GJA1, PSME2,PRG1, EXT1, DKFZP434J154, MVP, VASP, ARL7, NNMT, TAP1, PLOD2, ATF3,PALM2-AKAP2, IL8, LOXL2, IL4R, DGKA, STC2, SEC61G, RGS3, F2R, TPM2,PSMB9, LOX, STC1, PTGER4, IL6, SMAD3, WNT5A, BDNF, TNFRSF1A, FLNC,DKFZP564K0822, FLOT1, PTRF, HLA-B, MGC4083, TNFRSF10B, PLAGL1, PNMA2,TFPI, LAT, GZMB, CYR61, PLAUR, FSCN1, ERP70, AF1Q, HIC, COL6A1, IFITM3,MAP1B, FLJ46603, RAFTLIN, RRAS, FTL, KIAA0877, MT1E, CDC10, DOCK2,TRIM22, RIS1, BCAT1, PRF1, DBN1, MT1K, TMSB10, FLJ10350, C1orf24, NME7,TMEM22, TPK1, COL5A2, ELK3, CYLD, ADAMTS1, EHD2, and ACTB, whoseexpression indicates chemosensitivity to Bleomycin.q) One or more of the gene sequences NOS2A, MUC1, TFF3, GP1BB, IGLL1,BATF, MYB, PTPRS, NEFL, AIP, CEL, DGKA, RUNX1, ACTR1A, and CLCNKA,preferably gene sequences PTMA, SSRP1, NUDC, CTSC, AP1G2, PSME2, LBR,EFNB2, SERPINA1, SSSCA1, EZH2, MYB, PRIM1, H2AFX, HMGA1, HMMR, TK2,WHSC1, DIAPH1, LAMB3, DPAGT1, UCK2, SERPINB1, MDN1, BRRN1, GOS2, RAC2,MGC21654, GTSE1, TACC3, PLEK2, PLAC8, HNRPD, and PNAS-4, and mostpreferably gene sequences SSRP1, NUDC, CTSC, AP1G2, PSME2, LBR, EFNB2,SERPINA1, SSSCA1, EZH2, MYB, PRIM1, H2AFX, HMGA1, HMMR, TK2, WHSC1,DIAPH1, LAMB3, DPAGT1, UCK2, SERPINB1, MDN1, BRRN1, GOS2, RAC2,MGC21654, GTSE1, TACC3, PLEK2, PLAC8, HNRPD, and PNAS-4, whoseexpression indicates chemosensitivity to Methyl-GAG.r) One or more of the gene sequences MSN, ITGA5, VIM, TNFAIP3, CSPG2,WNT5A, FOXF2, LOC94105, IFI16, LRRN3, FGFR1, DOCK10, LEPRE1, COL5A2, andADAMTS1, and most preferably gene sequences ITGA5, TNFAIP3, WNT5A,FOXF2, LOC94105, IFI16, LRRN3, DOCK10, LEPRE1, COL5A2, and ADAMTS1,whose expression indicates chemosensitivity to carboplatin.s) One or more of the gene sequences RPL18, RPL10A, RNPS1, ANAPC5,EEF1B2, RPL13A, RPS15, AKAP1, NDUFAB1, APRT, ZNF593, MRP63, IL6R, RPL13,SART3, RPS6, UCK2, RPL3, RPL17, RPS2, PCCB, TOMM20, SHMT2, RPLP0, GTF3A,STOML2, DKFZp564J157, MRPS2, ALG5, and CALML4, and most preferably genesequences RPL18, RPL10A, ANAPC5, EEF1B2, RPL13A, RPS15, AKAP1, NDUFAB1,APRT, ZNF593, MRP63, IL6R, SART3, UCK2, RPL17, RPS2, PCCB, TOMM20,SHMT2, RPLP0, GTF3A, STOML2, DKFZp564J157, MRPS2, ALG5, and CALML4,whose expression indicates chemosensitivity to 5-FU(5-Fluorouracil).t) One or more of the gene sequences ITK, KIFC1, VLDLR, RUNX1, PAFAH1B3,H1FX, RNF144, TMSNB, CRY1, MAZ, SLA, SRF, UMPS, CD3Z, PRKCQ, HNRPM,ZAP70, ADD1, RFC5, TM4SF2, PFN2, BMI1, TUBGCP3, ATP6V1B2, RALY, PSMC5,CD1D, ADA, CD99, CD2, CNP, ERG, MYL6, CD3E, CD1A, CD1B, STMN1, PSMC3,RPS4Y1, AKT1, TAL1, GNA15, UBE2A, TCF12, UBE2S, CCND3, PAX6, MDK, CAPG,RAG2, ACTN1, GSTM2, SATB1, NASP, IGFBP2, CDH2, CRABP1, DBN1, CTNNA1,AKR1C1, CACNB3, FARSLA, CASP2, CASP2, E2F4, LCP2, CASP6, MYB, SFRS6,GLRB, NDN, CPSF1, GNAQ, TUSC3, GNAQ, JARID2, OCRL, FHL1, EZH2, SMOX,SLC4A2, UFD1L, SEPW1, ZNF32, HTATSF1, SHD1, PTOV1, NXF1, FYB, TRIM28,BC008967, TRB@, TFRC, H1F0, CD3D, CD3G, CENPB, ALDH2, ANXA1, H2AFX,CD1E, DDX5, ABL1, CCNA2, ENO2, SNRPB, GATA3, RRM2, GLUL, TCF7, FGFR1,SOX4, MAL, NUCB2, SMA3, FAT, UNG, ARHGDIB, RUNX1, MPHOSPH6, DCTN1,SH3GL3, VIM, PLEKHC1, CD47, POLR2F, RHOH, ADD1, and ATP2A3, preferablygene sequences ITK, KIFC1, VLDLR, RUNX1, PAFAH1B3, H1FX, RNF144, TMSNB,CRY1, MAZ, SLA, SRF, UMPS, CD3Z, PRKCQ, HNRPM, ZAP70, ADD1, RFC5,TM4SF2, PFN2, BMI1, TUBGCP3, ATP6V1B2, RALY, PSMC5, CD1D, ADA, CD99,CD2, CNP, ERG, MYL6, CD3E, CD1A, CD1B, STMN1, PSMC3, RPS4Y1, AKT1, TAL1,GNA15, UBE2A, TCF12, UBE2S, CCND3, PAX6, MDK, CAPG, RAG2, ACTN1, GSTM2,SATB1, NASP, IGFBP2, CDH2, CRABP1, DBN1, CTNNA1, AKR1C1, CACNB3, FARSLA,CASP2, CASP2, E2F4, LCP2, CASP6, MYB, SFRS6, GLRB, NDN, CPSF1, GNAQ,TUSC3, GNAQ, JARID2, OCRL, FHL1, EZH2, SMOX, SLC4A2, UFD1L, SEPW1,ZNF32, HTATSF1, SHD1, PTOV1, NXF1, FYB, TRIM28, BC008967, TRB@, TFRC,H1F0, CD3D, CD3G, CENPB, ALDH2, ANXA1, H2AFX, CD1E, DDX5, ABL1, CCNA2,ENO2, SNRPB, GATA3, RRM2, GLUL, TCF7, FGFR1, SOX4, MAL, NUCB2, SMA3,FAT, UNG, ARHGDIB, RUNX1, MPHOSPH6, DCTN1, SH3GL3, VIM, PLEKHC1, CD47,POLR2F, RHOH, ADD1, and ATP2A3, and most preferably gene sequencesKIFC1, VLDLR, RUNX1, PAFAH1B3, H1FX, RNF144, TMSNB, CRY1, MAZ, SLA, SRF,UMPS, CD3Z, PRKCQ, HNRPM, ZAP70, ADD1, RFC5, TM4SF2, PFN2, BMI1,TUBGCP3, ATP6V1B2, CD1D, ADA, CD99, CD2, CNP, ERG, CD3E, CD1A, PSMC3,RPS4Y1, AKT1, TAL1, UBE2A, TCF12, UBE2S, CCND3, PAX6, RAG2, GSTM2,SATB1, NASP, IGFBP2, CDH2, CRABP1, DBN1, AKR1C1, CACNB3, CASP2, CASP2,LCP2, CASP6, MYB, SFRS6, GLRB, NDN, GNAQ, TUSC3, GNAQ, JARID2, OCRL,FHL1, EZH2, SMOX, SLC4A2, UFD1L, ZNF32, HTATSF1, SHD1, PTOV1, NXF1, FYB,TRIM28, BC008967, TRB@, H1F0, CD3D, CD3G, CENPB, ALDH2, ANXA1, H2AFX,CD1E, DDX5, CCNA2, ENO2, SNRPB, GATA3, RRM2, GLUL, SOX4, MAL, UNG,ARHGDIB, RUNX1, MPHOSPH6, DCTN1, SH3GL3, PLEKHC1, CD47, POLR2F, RHOH,and ADD1, whose expression indicates chemosensitivity to Rituximab(e.g., MABTHERA™).u) One or more of the gene sequences CCL21, ANXA2, SCARB2, MAD2L1BP,CAST, PTS, NBL1, ANXA2, CD151, TRAM2, HLA-A, CRIP2, UGCG, PRSS11, MME,CBR1, LGALS1, DUSP3, PFN2, MICA, FTH1, RHOC, ZAP128, PON2, COL5A2, CST3,MCAM, IGFBP3, MMP2, GALIG, CTSD, ALDH3A1, CSRP1, S100A4, CALD1, CTGF,CAPG, HLA-A, ACTN1, TAGLN, FSTL1, SCTR, BLVRA, COPEB, DIPA, SMARCD3,FN1, CTSL, CD63, DUSP1, CKAP4, MVP, PEA15, S100A13, and ECE1, preferablygene sequences TRA1, ACTN4, WARS, CALM1, CD63, CD81, FKBP1A, CALU,IQGAP1, CTSB, MGC8721, STAT1, TACC1, TM4SF8, CD59, CKAP4, DUSP1, RCN1,MGC8902, LGALS1, BHLHB2, RRBP1, PKM2, PRNP, PPP2CB, CNN3, ANXA2, ER3,JAK1, MARCKS, LUM, FER1L3, SLC20A1, EIF4G3, HEXB, EXT1, TJP1, CTSL,SLC39A6, RIOK3, CRK, NNMT, COL1A1, TRAM2, ADAM9, DNAJC7, PLSCR1, PRSS23,PLOD2, NPC1, TOB1, GFPT1, IL8, DYRK2, PYGL, LOXL2, KIAA0355, UGDH,NFIL3, PURA, ULK2, CENTG2, NID2, CAP350, CXCL1, BTN3A3, IL6, WNT5A,FOXF2, LPHN2, CDH11, P4HA1, GRP58, ACTN1, CAPN2, DSIPI, MAP1LC3B, GALIG,IGSF4, IRS2, ATP2A2, OGT, TNFRSF10B, KIAA1128, TM4SF1, RBPMS, RIPK2,CBLB, NR1D2, BTN3A2, SLC7A11, MPZL1, IGFBP3, SSA2, FN1, NQO1, ASPH,ASAH1, MGLL, SERPINB6, HSPA5, ZFP36L1, COL4A2, COL4A1, CD44, SLC39A14,NIPA2, FKBP9, IL6ST, DKFZP564G2022, PPAP2B, MAP1B, MAPK1, MYO1B, CAST,RRAS2, QKI, LHFPL2, 38970, ARHE, KIAA1078, FTL, KIAA0877, PLCB1,KIAA0802, KPNB1, RAB3GAP, SERPINB1, TIMM17A, SOD2, HLA-A, NOMO2,LOC55831, PHLDA1, TMEM2, MLPH, FAD104, LRRC5, RAB7L1, FLJ35036, DOCK10,LRP12, TXNDC5, CDCl₄B, HRMT1L1, CORO1C, DNAJC10, TNPO1, LONP, AMIGO2,DNAPTP6, and ADAMTS1, and most preferably gene sequences TRA1, ACTN4,CALM1, CD63, FKBP1A, CALU, IQGAP1, MGC8721, STAT1, TACC1, TM4SF8, CD59,CKAP4, DUSP1, RCN1, MGC8902, LGALS1, BHLHB2, RRBP1, PRNP, IER3, MARCKS,LUM, FER1L3, SLC20 μl, HEXB, EXT1, TJP1, CTSL, SLC39A6, RIOK3, CRK,NNMT, TRAM2, ADAM9, DNAJC7, PLSCR1, PRSS23, PLOD2, NPC1, TOB1, GFPT1,IL8, PYGL, LOXL2, KIAA0355, UGDH, PURA, ULK2, CENTG2, NID2, CAP350,CXCL1, BTN3A3, IL6, WNT5A, FOXF2, LPHN2, CDH11, P4HA1, GRP58, DSIPI,MAP1LC3B, GALIG, IGSF4, IRS2, ATP2A2, OGT, TNFRSF10B, KIAA1128, TM4SF1,RBPMS, RIPK2, CBLB, NR1D2, SLC7A11, MPZL1, SSA2, NQO1, ASPH, ASAH1,MGLL, SERPINB6, HSPA5, ZFP36L1, COL4A1, CD44, SLC39A14, NIPA2, FKBP9,IL6ST, DKFZP564G2022, PPAP2B, MAP1B, MAPK1, MYO1B, CAST, RRAS2, QKI,LHFPL2, 38970, ARHE, KIAA1078, FTL, KIAA0877, PLCB1, KIAA0802, RAB3GAP,SERPINB1, TIMM17A, SOD2, HLA-A, NOMO2, LOC55831, PHLDA1, TMEM2, MLPH,FAD104, LRRC5, RAB7L1, FLJ35036, DOCK10, LRP12, TXNDC5, CDCl₄B, HRMT1L1,CORO1C, DNAJC10, TNPO1, LONP, AMIGO2, DNAPTP6, and ADAMTS1, whoseexpression indicates sensitivity to radiation therapy.v) One or more of the gene sequences FAU, NOL5A, ANP32A, ARHGDIB, LBR,FABP5, ITM2A, SFRS5, IQGAP2, SLC7A6, SLA, IL2RG, MFNG, GPSM3, PIM2,EVER1, LRMP, ICAM2, RIMS3, FMNL1, MYB, PTPN7, LCK, CXorf9, RHOH,ZNFN1A1, CENTB1, LCP2, DBT, CEP1, IL6R, VAV1, MAP4K1, CD28, PTP4A3,CD3G, LTB, USP34, NVL, CD8B1, SFRS6, LCP1, CXCR4, PSCDBP, SELPLG, CD3Z,PRKCQ, CD1A, GATA2, P2RX5, LAIR1, C1orf38, SH2D1A, TRB@, SEPT6, HA-1,DOCK2, WBSCR20C, CD3D, RNASE6, SFRS7, WBSCR20A, NUP210, CD6, HNRPA1,AIF1, CYFIP2, GLTSCR2, C11orf2, ARHGAP15, BIN2, SH3TC1, STAG3, TM6SF1,C15orf25, FLJ22457, PACAP, and MGC2744, whose expression indicatessensitivity to an HDAC inhibitor.w) One or more of the gene sequences CD99, SNRPA, CUGBP2, STAT5A, SLA,IL2RG, GTSE1, MYB, PTPN7, CXorf9, RHOH, ZNFN1A1, CENTB1, LCP2, HIST1H4C,CCR7, APOBEC3B, MCM7, LCP1, SELPLG, CD3Z, PRKCQ, GZMB, SCN3A, LAIR1,SH2D1A, SEPT6, CG018, CD3D, C18orf10, PRF1, AIF1, MCM5, LPXN, C22orf18,ARHGAP15, and LEF1, whose expression indicates sensitivity to5-Aza-2′-deoxycytidine (Decitabine).

Probes that may be employed on microarrays of the invention includeoligonucleotide probes having sequences complementary to any of thebiomarker gene or microRNA sequences described above. Additionally,probes employed on microarrays of the invention may also includeproteins, peptides, or antibodies that selectively bind any of theoligonucleotide probe sequences or their complementary sequences.Exemplary probes are listed in Tables 22-44, wherein for each treatmentlisted, the biomarkers indicative of treatment sensitivity, thecorrelation of biomarker expression to growth inhibition, and thesequence of an exemplary probe (Tables 22-44) to detect biomarker(Tables 1-21) expression are shown.

Identification of Biomarker Genes

The gene expression measurements of the NCI60 cancer cell lines wereobtained from the National Cancer Institute and the MassachusettsInstitute of Technology (MIT). Each dataset was normalized so thatsample expression measured by different chips could be compared. Thepreferred method of normalization is the logit transformation, which isperformed for each gene y on each chip:

logit(y)=log[(y−background)/(saturation−y)],

where background is calculated as the minimum intensity measured on thechip minus 0.1% of the signal intensity range: min-0.001*(max-min), andsaturation is calculated as the maximum intensity measured on the chipplus 0.1% of the signal intensity range: max+0.001*(max-min). Theresulting logit transformed data is then z-transformed to mean zero andstandard deviation 1.

Next, gene expression is correlated to cancer cell growth inhibition.Growth inhibition data (GI50) of the NCI60 cell lines in the presence ofany one of thousands of tested compounds was obtained from the NCI. Thecorrelation between the logit-transformed expression level of each genein each cell line and the logarithm of GI50 (the concentration of agiven compound that results in a 50% inhibition of growth) can becalculated, e.g., using the Pearson correlation coefficient or theSpearman Rank-Order correlation coefficient. Instead of using GI50s, anyother measure of patient sensitivity to a given compound may becorrelated to the patient's gene expression. Since a plurality ofmeasurements may be available for a single gene, the most accuratedetermination of correlation coefficient was found to be the median ofthe correlation coefficients calculated for all probes measuringexpression of the same gene.

The median correlation coefficient of gene expression measured on aprobe to growth inhibition or patient sensitivity is calculated for allgenes, and genes that have a median correlation above 0.3, 0.4, 0.5,0.6, 0.7, 0.8, 0.9, 0.95, or 0.99 are retained as biomarker genes.Preferably, the correlation coefficient of biomarker genes will exceed0.3. This is repeated for all the compounds to be tested. The result isa list of marker genes that correlates to sensitivity for each compoundtested.

Predicting Patient Sensitivity or Resistance to Medical Treatment

For a given compound, the biomarker whose expression has been shown tocorrelate to chemosensitivity can be used to classify a patient, e.g., acancer patient, as sensitive to a medical treatment, e.g.,administration of a chemotherapeutic agent or radiation. Using a tumorsample or a blood sample (e.g., in case of leukemia or lymphoma) from apatient, expression of the biomarker in the cells of the patient in thepresence of the treatment agent is determined (using, for example, anRNA extraction kit, a DNA microarray and a DNA microarray scanner). Thebiomarker expression measurements are then logit transformed asdescribed above. The sum of the expression measurements of thebiomarkers is then compared to the median of the sums derived from atraining set population of patients having the same tumor. If the sum ofbiomarker expression in the patient is closest to the median of the sumsof expression in the surviving members of the training set, the patientis predicted to be sensitive to the compound or other medical treatment.If the sum of expression in the patient is closest to the median of thesums of expression in the non-surviving members of the training set, thepatient is predicted to be resistant to the compound.

Machine learning techniques such as Neural Networks, Support VectorMachines, K Nearest Neighbor, and Nearest Centroids may also be employedto develop models that discriminate patients sensitive to treatment fromthose resistant to treatment using biomarker expression as modelvariables which assign each patient a classification as resistant orsensitive. Machine learning techniques used to classify patients usingvarious measurements are described in U.S. Pat. No. 5,822,715; U.S.Patent Application Publication Nos. 2003/0073083, 2005/0227266,2005/0208512, 2005/0123945, 2003/0129629, and 2002/0006613; and inVapnik V N. Statistical Learning Theory, John Wiley & Sons, New York,1998; Hastie et al., 2001, The Elements of Statistical Learning: DataMining, Inference, and Prediction, Springer, N.Y.; Agresti, 1996, AnIntroduction to Categorical Data Analysis, John Wiley & Sons, New York;and V. Tresp et al., “Neural Network Modeling of PhysiologicalProcesses”, in Hanson S. J. et al. (Eds.), Computational Learning Theoryand Natural Learning Systems 2, MIT Press, 1994, hereby incorporated byreference.

Other variables can be used to determine relative biomarker expressionbetween a patient (e.g., a cancer patient) and a normal subject (e.g., acontrol subject), including but not limited to, measurement of biomarkerDNA copy number and the identification of biomarker genetic mutations.

A more compact microarray can be designed using only the oligonucleotideprobes having measurements yielding the median correlation coefficientswith cancer cell growth inhibition. Thus, in this embodiment, only oneprobe needs to be used to measure expression of each biomarker.Biomarkers include polypeptides and metabolites thereof. A skilledartisan can use employ assays that measure changes in polypeptidebiomarker expression (e.g., Western blot, immunofluorescent staining,and flow cytometry) to determine a patient's sensitivity to a treatment(e.g., chemotherapy, radiation therapy, or surgery).

Identifying a Subpopulation of Patients Sensitive to a Treatment forCancer

The invention can also be used to identify a subpopulation of patients,e.g., cancer patients, that are sensitive to a compound or other medicaltreatment previously thought to be ineffective for the treatment ofcancer. To this end, genes or microRNAs whose expression correlates tosensitivity to a compound or other treatment can be identified so thatpatients sensitive to a compound or other treatment may be identified.To identify such biomarkers, gene or microRNA expression within celllines can be correlated to the growth of those cell lines in thepresence of the same compound or other treatment. Preferably, genes ormicroRNAs whose expression correlates to cell growth with a correlationcoefficient exceeding 0.3 may be considered possible biomarkers.

Alternatively, genes or microRNAs can be identified as biomarkersaccording to their ability to discriminate patients known to besensitive to a treatment from those known to be resistant. Thesignificance of the differences in gene or microRNA expression betweenthe sensitive and resistant patients may be measured using, e.g.,t-tests. Alternatively, naïve Bayesian classifiers may be used toidentify gene biomarkers that discriminate sensitive and resistantpatient subpopulations given the gene expressions of the sensitive andresistant subpopulations within a treated patient population.

The patient subpopulations considered can be further divided intopatients predicted to survive without treatment, patients predicted todie without treatment, and patients predicted to have symptoms withouttreatment. The above methodology may be similarly applied to any ofthese further defined patient subpopulations to identify biomarkers ableto predict a subject's sensitivity to compounds or other treatments forthe treatment of cancer.

Patients with elevated expression of biomarkers correlated tosensitivity to a compound or other medical treatment would be predictedto be sensitive to that compound or other medical treatment.

The invention is particularly useful for recovering compounds or othertreatments that failed in clinical trials by identifying sensitivepatient subpopulations using the gene or microRNA expression methodologydisclosed herein to identify biomarkers that can be used to predictclinical outcome.

Kit, Apparatus, and Software for Clinical Use

This invention can also be used to predict patients who are resistant orsensitive to a particular treatment by using a kit that includes a kitfor RNA extraction from tumors (e.g., Trizol from Invitrogen Inc.), akit for RNA amplification (e.g., MessageAmp from Ambion Inc.), amicroarray for measuring biomarker expression (e.g., HG-U133A GeneChipfrom Affymetrix Inc.), a microarray hybridization station and scanner(e.g., GeneChip System 3000Dx from Affymetrix Inc.), and software foranalyzing the expression of marker genes as described in herein (e.g.,implemented in R from R-Project or S-Plus from Insightful Corp.).

Methodology of the In Vitro Cancer Growth Inhibition Screen

The human tumor cell lines of the cancer screening panel are grown inRPMI 1640 medium containing 5% fetal bovine serum and 2 mM L-glutamine.Cells are inoculated into 96 well microtiter plates in 100 μL at platingdensities ranging from 5,000 to 40,000 cells/well depending on thedoubling time of individual cell lines. After cell inoculation, themicrotiter plates are incubated at 37° C., 5% CO₂, 95% air, and 100%relative humidity for 24 hrs prior to addition of experimentalcompounds.

After 24 hrs, two plates of each cell line are fixed in situ with TCA,to represent a measurement of the cell population for each cell line atthe time of compound addition (Tz). Experimental compounds aresolubilized in dimethyl sulfoxide at 400-fold the desired final maximumtest concentration and stored frozen prior to use. At the time ofcompound addition, an aliquot of frozen concentrate is thawed anddiluted to twice the desired final maximum test concentration withcomplete medium containing 50 μg/mL Gentamicin. Additional four, 10-foldor V2 log serial dilutions are made to provide a total of five compoundconcentrations plus control. Aliquots of 100 μL of these differentcompound dilutions are added to the appropriate microtiter wells alreadycontaining 100 μL of medium, resulting in the required final compoundconcentrations.

Following compound addition, the plates are incubated for an additional48 hrs at 37° C., 5% CO₂, 95% air, and 100% relative humidity. Foradherent cells, the assay is terminated by the addition of cold TCA.Cells are fixed in situ by the gentle addition of 50 μL of cold 50%(w/v) TCA (final concentration, 10% TCA) and incubated for 60 min at 4°C. The supernatant is discarded, and the plates are washed five timeswith tap water and air-dried. Sulforhodamine B (SRB) solution (100 μL)at 0.4% (w/v) in 1% acetic acid is added to each well, and plates areincubated for 10 min at room temperature. After staining, unbound dye isremoved by washing five times with 1% acetic acid and the plates areair-dried. Bound stain is subsequently solubilized with 10 mM trizmabase, and the absorbance is read on an automated plate reader at awavelength of 515 nm. For suspension cells, the methodology is the sameexcept that the assay is terminated by fixing settled cells at thebottom of the wells by gently adding 50 μL of 80% TCA (finalconcentration, 16% TCA). Using the seven absorbance measurements [timezero, (Tz), control growth, (C), and test growth in the presence ofcompound at the five concentration levels (Ti)], the percentage growthis calculated at each of the compound concentrations levels. Percentagegrowth inhibition is calculated as:

[(Ti−Tz)/(C−Tz)]×100 for concentrations for which Ti>/=Tz

[(Ti−Tz)/Tz]×100 for concentrations for which Ti<Tz

Three dose response parameters are calculated for each experimentalagent. Growth inhibition of 50% (GI50) is calculated from[(Ti−Tz)/(C−Tz)]×100=50, which is the compound concentration resultingin a 50% reduction in the net protein increase (as measured by SRBstaining) in control cells during the compound incubation. The compoundconcentration resulting in total growth inhibition (TGI) is calculatedfrom Ti=Tz. The LC50 (concentration of compound resulting in a 50%reduction in the measured protein at the end of the compound treatmentas compared to that at the beginning) indicating a net loss of cellsfollowing treatment is calculated from [(Ti−Tz)/Tz]×100=−50. Values arecalculated for each of these three parameters if the level of activityis reached; however, if the effect is not reached or is exceeded, thevalue for that parameter is expressed as greater or less than themaximum or minimum concentration tested.

RNA Extraction and Gene Expression Measurement

Cell/tissue samples are snap frozen in liquid nitrogen until processing.RNA is extracted using e.g., Trizol Reagent (Invitrogen) followingmanufacturers instructions. RNA is amplified using e.g., MessageAmp kit(Ambion) following manufacturers instructions. Amplified RNA isquantified using e.g., HG-U133A GeneChip (Affymetrix) and compatibleapparatus e.g., GCS3000Dx (Affymetrix), using manufacturersinstructions.

The resulting gene expression measurements are further processed asdescribed in this document. The procedures described can be implementedusing R software available from R-Project and supplemented with packagesavailable from Bioconductor.

For many drugs 10-30 biomarkers are sufficient to give an adequateresponse, thus, given the relatively small number of biomarkersrequired, procedures, such as quantitative reverse transcriptasepolymerase chain reaction (qRT-PCR), can be performed to measure, withgreater precision, the amount of biomarker genes expressed in a sample.This will provide an alternative to or a complement to microarrays sothat a single companion test, typically more quantitative thanmicroarrays alone, employing biomarkers of the invention can be used topredict sensitivity to a new drug. qRT-PCR can be performed alone or incombination with a microarray described herein. Procedures forperforming qRT-PCR are described in, e.g., U.S. Pat. No. 7,101,663 andU.S. Patent Application Nos. 2006/0177837 and 2006/0088856. The methodsof the invention are readily applicable to newly discovered drugs aswell as drugs described herein.

The following examples are provided so that those of ordinary skill inthe art can see bow to use the methods and kits of the invention. Theexamples are not intended to limit the scope of what the inventorregards as their invention.

EXAMPLES Example 13 Identification of Gene Biomarkers forChemosensitivity to Common Chemotherapy Drugs

DNA chip measurements of the 60 cancer cell lines of the NCI60 data setwere downloaded from the Broad Institute (Cambridge, Mass.) and logitnormalized. Growth inhibition data of thousands of compounds against thesame cell lines were downloaded from the National Cancer Institute.Compounds where the difference concentration to achieve 50% in growthinhibition (GI50) was less than 1 log were deemed uninformative andrejected. Each gene's expression in each cell line was correlated to itsgrowth (−log(GI50)) in those cell lines in the presence of a givencompound. The median Pearson correlation coefficient was used whenmultiple expression measurements were available for a given gene, andgenes having a median correlation coefficient greater than 0.3 wereidentified as biomarkers for a given compound.

Example 2 Prediction of Treatment Sensitivity for Brain Cancer Patients

DNA chip measurements of gene expression in tumors from 60 brain cancerpatients were downloaded from the Broad Institute. All data files werelogit normalized. For each of the common chemotherapy drugs Cisplatin,Vincristine, Adriamycine, Etoposide, Aclarubicine, Mitoxantrone andAzaguanine, the gene expression for the marker genes was summed. The sumwas normalized by dividing by the standard deviation of all patients andcompared to the median of the sums of patients who survived and themedian of the sums of patients who died:

$\mspace{79mu} {{{NormalizedSum}\; ({compound})} = \frac{{sum}\; \left( {{marker}\mspace{14mu} {genes}\mspace{14mu} {for}\mspace{14mu} {compound}} \right)}{{sd}\; \left( {{sums}\mspace{14mu} {of}\mspace{14mu} {all}\mspace{14mu} {patients}} \right)}}$${{Sensitivity}({compound})} = {\begin{bmatrix}{{{NormalizedSum}\; ({compound})} -} \\{{median}\left( {{NormalizedSumdeadpatients}\mspace{11mu} ({compound})} \right)}\end{bmatrix}^{2} - \begin{bmatrix}{{{NormalizedSum}\; ({compound})} -} \\{{median}\left( {{NormalizedSumsurvivingpatients}\mspace{11mu} ({compound})} \right)}\end{bmatrix}^{2}}$

FIGS. 2 and 3 show the resulting treatment sensitivity predictions fortwo of the 60 patients. All patients received Cisplatin and theprediction of survival amongst the 60 patients based on their Cisplatinchemosensitivity yielded the Kaplan-Meier survival curve shown in FIG.4. The expression of the 16 Cisplatin biomarker genes was first reducedto 5 components (dimensions) using Independent Component Analysis(fastICA). Five different classification methods were trained on thefive components from the 60 patients: K Nearest Neighbor with K=1, KNearest Neighbor with K=3, Nearest Centroid, Support Vector Machine, andNeural Network. Chemosensitivity or sensitivity to radiation treatmentwas predicted by combining the classifications of the five methodswherein each classification method was assigned a single vote: unanimouschemosensitive/treatment sensitive prediction resulted in a predictionof chemosensitive/treatment sensitive. All other predictions resulted ina prediction of chemoresistant/treatment resistant. The performance ofthe combined classifier was validated using leave-one-out crossvalidation and the survival of the two predicted groups shown in FIG. 4.The survival rate of the patients predicted to be chemosensitive washigher than the patients predicted to be chemoresistant.

Example 3 Prediction of Chemosensitivity for Lymphoma (DLBCL) Patients

DNA chip measurements of gene expression in the tumors from 56 DLBCL(diffuse large B-cell lymphoma) patients were downloaded from the BroadInstitute. All data files were logit normalized. All patients receivedVincristine and Adriamycine and the prediction of survival amongst the56 patients based on their Vincristine and Adriamycine chemosensitivityyielded the Kaplan-Meier survival curve shown in FIG. 5. The expressionof the 33 Vincristine genes and 16 Adriamycine genes was first reducedto 3 components (dimensions) using Independent Component Analysis(fastICA). Five different classification methods were trained on theindependent components from the 56 patients: K Nearest Neighbor withK=1, K Nearest Neighbor with K=3, Nearest Centroid, Support VectorMachine, and Neural Network. Chemosensitivity was predicted by combiningthe classifications of the five methods wherein each classificationmethod was assigned a single vote: unanimous chemosensitive predictionresulted in a prediction of chemosensitive. All other predictionsresulted in a prediction of chemoresistant. The performance of thecombined classifier was validated using leave-one-out cross validationand the survival of the two predicted groups is shown in FIG. 5. Thesurvival rate of the patients predicted to be chemosensitive was higherthan the patients predicted to be chemoresistant.

Example 4 Prediction of Chemosensitivity for Lung Cancer Patients

DNA chip measurements of gene expression in the tumors from 86 lungcancer (adenocarcinoma) patients was downloaded from the University ofMichigan, Ann Arbor. Of the 86 patients, 19 had Stage III of the diseaseand received adjuvant chemotherapy. Raw data was logit normalized.Instead of the combined classifier described for the brain cancer andlymphoma examples above, the sum of biomarker gene expression wascalculated for each patient and used to discriminate chemosensitive andchemoresistant patients. For each patient, the gene expression of the 16marker genes for Cisplatin sensitivity (all Stage III patients receivedCisplatin after surgery) was summed. If the sum was closer to the medianof the sums of the surviving patients, the patient was predicted to besensitive to Cisplatin. If the sum was closest to the median of the sumsof the non-surviving patients, the patient was predicted to be resistantto Cisplatin. The survival rates of the two predicted groups are shownin FIG. 6. The survival rate of the patients predicted to bechemosensitive was higher than the patients predicted to bechemoresistant.

Example 5 Prediction of Rituximab Sensitivity for Lymphoma (DLBCL)Patients

The method is not limited to cytotoxic chemicals. It is also applicableto predicting the efficacy of protein therapeutics, such as monoclonalantibodies, approved for treating cancer. For example, the monoclonalantibody Rituximab (e.g., MABTHERA™ and RITUXAN™) was examined. Data forcytotoxicity of Rituximab in cell lines in vitro were obtained frompublished reports (Ghetie et al., Blood 97(5):1392-1398, 2001). Thiscytotoxicity in each cell line was correlated to the expression of genesin these cell lines (downloaded from the NCBI Gene Expression Omnibusdatabase using accession numbers GSE2350, GSE1880, GDS181). Theidentified marker genes were used to predict the sensitivity of DLBCL toRituximab in a small set of 14 patients treated with Rituximab andCHOP(R—CHOP) (downloaded from NCBI Gene Expression Omnibus underaccession number GSE4475). Conversion between different chip types wasperformed using matching tables available through Affymetrix.

The survival of patients predicted to be sensitive to be R-CHOP iscompared to the survival of patients predicted to be resistant to R-CHOPin FIG. 7. The survival rate of the patients predicted to bechemosensitive was higher than the patients predicted to bechemoresistant.

To predict the sensitivity toward combination therapies, such as thoseused to treat Diffuse Large B-cell Lymphoma (DLBCL), patient sensitivityto a particular combination therapy is predicted by combining the markergenes for the individual compounds used in the combination. An exampleof this is shown in FIG. 8, where the predicted sensitivities of onepatient towards a number of combination therapies used against DLBCL(identified by their acronyms) are shown: R-CHOP contains Rituximab(e.g., MABTHERA™), Vincristine, Doxorubicin (Adriamycin),Cyclophosphamide, and Prednisolone; R-ICE contains Rituximab,Ifosfamide, Carboplatin, and Etoposide; R-MIME contains Rituximab,Mitoguazone, Ifosfamide, Methotrexate, and Etoposide; CHOEP containsCyclophosphamide, Doxorubicin, Etoposide, Vincristine and Prednisone;DHAP contains Dexamethasone, Cytarabine (Ara C), and Cisplatin; ESHAPcontains Etoposide, Methylprednisolone (Solumedrol), Cytarabine (Ara-C)and Cisplatin; and HOAP-Bleo contains Doxorubicin, Vincristine, Ara C,Prednisone, and Bleomycin.

Example 6 Prediction of Radiosensitivity for Brain Tumor(Medulloblastoma) Patients

The method of identifying biomarkers can also be applied to other formsof treatment such as radiation therapy. For example, sensitivity toradiation therapy was predicted for brain tumor patients. Radiationtherapy in the form of craniospinal irradiation yielding 2,400-3,600centigray (cGy) with a tumor dose of 5,300-7,200 cGy was administered tothe brain tumor patients using a medical device that emits beams ofradiation. Sensitivity of the 60 cancer cell lines used in the NCI60dataset to radiation treatment was obtained from published reports. Thissensitivity was correlated to the expression of genes in the cell linesas described above to identify marker genes. DNA microarray measurementsof gene expression in brain tumors obtained from patients subsequentlytreated with radiation therapy were obtained from the Broad Institute.The identified gene biomarkers were used to classify the patients assensitive or resistant to radiation therapy. The survival of thepatients in the two predicted categories is shown in FIG. 9. Thesurvival rate of the patients predicted to be sensitive to radiationtherapy was higher than the patients predicted to be resistant toradiation therapy.

Example 7 Drug Rescue

Every member of a population may not be equally responsive to aparticular treatment. For example, new compounds often fail in lateclinical trials because of lack of efficacy in the population tested.While such compounds may not be effective in the overall population,there may be subpopulations sensitive to those failed compounds due tovarious reasons, including inherent differences in gene expression. Themethod as described herein can be used to rescue failed compounds byidentifying a patient subpopulation sensitive to a compound using theirgene expression as an indicator. Subsequent clinical trials restrictedto a sensitive patient subpopulation may demonstrate efficacy of apreviously failed compound within that particular patient subpopulation,advancing the compound towards approval for use in that subpopulation.

To this end, in vitro measurements of the inhibitory effects of acompound on various cancer cell lines are compared to the geneexpression of cells. The growth of the cancer cell samples can becorrelated to gene expression measurements as described above. This willidentify marker genes that can be used to predict patient sensitivity tothe failed compound. Once biomarkers are identified, the expression ofbiomarker genes in cells obtained from patients can be measuredaccording to the procedure detailed above. The patients are predicted tobe responsive or non-responsive to compound treatment according to theirgene biomarker expression profile. Clinical effect must then bedemonstrated in the group of patients that are predicted to be sensitiveto the failed compound.

The method may be further refined if patients responsive to the compoundtreatment are further subdivided into those predicted to survive withoutthe compound and those predicted to die or suffer a relapse without thecompound. Clinical efficacy in the subpopulation that is predicted todie or suffer relapse can be further demonstrated. Briefly, the geneexpression at the time of diagnosis of patients who later die from theirdisease is compared to gene expression at the time of diagnosis ofpatients who are still alive after a period of time (e.g., 5 years).Genes differentially expressed between the two groups are identified asprospective biomarkers and a model is built using those gene biomarkersto predict treatment efficacy.

Examples of compounds that have failed in clinical trials includeGefinitib (e.g., Iressa, AstraZeneca) in refractory, advancednon-small-cell lung cancer (NSCLC), Bevacizumab (e.g., Avastin,Genentech) in first-line treatment for advanced pancreatic cancer,Bevacizumab (e.g., Avastin, Genentech) in relapsed metastatic breastcancer patients, and Erlotinib (e.g., Tarceva, Genentech) in metastaticnon-small cell lung cancer (NSCLC). The method of the invention may beapplied to these compounds, among others, so that sensitive patientsubpopulations responsive to those compounds may be identified.

Example 8 Median of the Correlations Versus Correlation of the Median

The median of the correlations of the individual probe measurements tocancer cell growth as employed by the invention was compared to thecorrelation of the median probe measurements: this will determine atwhich step of the method a median calculation should be performed. Inthe former, several correlations are calculated for each gene sincemultiple probes measure a given gene's expression, but only the medianof the correlation coefficients is finally retained to identifybiomarkers. In the latter, only one correlation is calculated for eachgene because only the median gene expression measurement is consideredfor each gene. FIG. 10 shows the results of using the correlation of themedian expression measurements to identify biomarker genes of radiationsensitivity predicting the survival of 60 brain cancer patients. Thedifference in survival between the group predicted to be radiationsensitive and the group predicted to be radiation resistant in FIG. 10is much smaller than the difference depicted in FIG. 9 which employed amedian correlation coefficient suggesting that the invention's median ofthe correlations employed in FIG. 9 outperforms the correlation of themedian depicted in FIG. 10.

If we look at individual marker genes like OMD, the median of thecorrelation to measured radiosensitivity of cell lines in vitro is 0.32.The correlation of the median, however, is 0.39. Adjusting the cutofffrom 0.3 to 0.4 to compensate for the difference does not improve onFIG. 10, however.

We have also compared median correlation to weighted voting as proposedby Staunton et al., PNAS 98(19):10787-10792, 2001). Weighted votingproduced a poor result similar to that of FIG. 10, with a P-value of0.11.

Example 9 Other Methods of Identifying Biomarkers

The examples shown above all rely on the availability of measurements ofinhibition by a compound or treatment of the growth of cell lines invitro. Such measurements may not always be available or practical. Inthat case an alternative method of identifying biomarkers can beemployed. If the target(s) of the compound is/are known, it is possibleto build a model based on the gene expression of the known target(s).One example is the drug sunitinib (SU11248), for which eight targets areknown. Sunitinib inhibits at least eight receptor protein-tyrosinekinases including vascular endothelial growth factor receptors 1-3(VEGFR1-VEGFR3), platelet-derived growth factor receptors (PDGFRA andPDGFRB), stem cell factor receptor (Kit), Flt-3, and colony-stimulatingfactor-1 receptor (CSF-1R). U.S. Patent Application Publication2006/0040292 mentions prediction of response measuring just two targets,PDGFRA and KIT. Using the sum of the gene expression of four targets itis possible to predict with more reliability the response to sunitinib.As an example, the predicted sunitinib sensitivity of cell lines HT29,U118, 786, and H226 is 0.24, 2.3, 0.14 and 0.60, respectively, based onthe sum of the four targets PDGFRB, KDR, KIT and FLT3. This correlateswell with the measured response in mouse xenografts of these cells(correlation coefficient 0.86) as well as with the measuredanti-angiogenetic effect measured in mouse xenografts (Potapova et al.Contribution of individual targets to the antitumor efficacy of themultitargeted receptor tyrosine kinase inhibitor SU11248 (Mol. Cancer.Ther. 5(5):1280-9, 2006). This is better than a model based only on twotargets PDGFRA and KIT (correlation coefficient 0.56).

This four-gene predictor of sunitinib response can be applied to a largenumber of tumor samples from patients with different tumors from whichgene expression analysis has been performed in order to get an idea ofthe range of sensitivities within each cancer type as well as whichcancer types are most susceptible to treatment with sunitinib. FIG. 11shows just a small fraction of the cancer samples available fromwww.intgen.org/expo.html. The comparison is based on normalizing thesamples in such a way (e.g., logit normalization) that different cancertypes become comparable. Sunitinib is currently approved by the FDA forrenal cancer and gastrointestinal cancer. Both kidney and colon show agood response in this plot.

Any other drug response predictor based on gene expression can be testedin the same manner as shown in FIG. 11.

The approach of identifying biomarkers based on known targets can alsobe applied to RNA antagonists such as SPC2996 targeted against Bcl-2. Aresponse predictor can be built based on measuring the gene expressionof Bcl-2 in samples from cancer patients. The same approach can be usedfor the targets of all mRNA antagonists or inhibitors.

Example 10 Identifying Candidate Drugs for a Known Target

The methods of the invention described herein can also be used foridentifying candidate drugs to a known target. Basically, the method ofidentifying biomarkers is run backwards in order to identify candidatedrugs. If one starts with a known target, the expression of itscorresponding gene is determined in the NCI 60 cell lines and correlatedto the measured growth inhibition of all the thousands of drugs testedin the NCI 60 cell lines. This provides a list, ranked by correlationcoefficient, of candidate drugs for the target. It is even possible totest new drugs and compare their correlation coefficient to the targetgene expression to the correlation coefficients of the already testeddrugs.

Example 11 Using MicroRNAs as Biomarkers of Drug Response

In recent years it has become clear that microRNAs (miRNA) play animportant role in regulating the translation of mRNAs. As such,microRNAs may contain important information relevant for the predictionof drug sensitivity. This information may be complementary to theinformation contained in mRNA expression. Shown below is the correlationbetween predicted and measured chemosensitivity of the NCI 60 celllines. The prediction is based either on mRNA measurements with DNAmicroarrays as described herein or predictions based on measurements ofmicroRNA concentration (ArrayExpress accession number E-MEXP-1029) usinga microRNA specific microarray (ArrayExpress accession numberA-MEXP-620). Whenever more than one probe is used to determine theconcentration of a given microRNA, the median correlation procedure isused for calculating correlation between microRNA concentration and−log(GI50).

miRNA mRNA Combined cisplatin 0.16 0.02 0.21 PXD101 0.44 0.31 0.50vincristine 0.06 0.11 0.26 etoposide 0.32 0.41 0.44 adriamycine 0.240.22 0.28As the above table shows, the correlation (determined usingleave-one-out cross-validation) is highest when using a combination(linear sum) of microRNA and mRNA predictions. These results suggestthat a more accurate drug response predictor can be built using acombination of microRNA and mRNA. It is possible to measure both in thesame experiment, as long as one takes into consideration that microRNAsin general do not have a polyA tail as mRNA does. Only slightmodifications to the amplification and labeling methods used for mRNAmay be needed to incorporate microRNAs into the analysis. Commercialkits for microRNA extraction, amplification, and labeling are availablefrom suppliers (e.g., Ambion Inc.).

Tables 22A-76A list the microRNA probes that are useful for detection ofsensitivity to individual drugs, as determined by their mediancorrelation to −log(GI50) for the indicated drug.

OTHER EMBODIMENTS

All publications and patent applications mentioned in this specificationare herein incorporated by reference to the same extent as if eachindependent publication or patent application was specifically andindividually indicated to be incorporated by reference. While theinvention has been described in connection with specific embodimentsthereof, it will be understood that it is capable of furthermodifications and this application is intended to cover any variations,uses, or adaptations of the invention following, in general, theprinciples of the invention and including such departures from thepresent disclosure that come within known or customary practice withinthe art to which the invention pertains and may be applied to theessential features hereinbefore set forth.

Legend:

List_(—)2006: biomarkers identified in 2006 using the new U133A chipmeasurementsList_(—)2005: biomarkers listed in 2005 patent filingHU6800: biomarkers obtained with old HU6800 chip measurementsList_Prior: matching biomakrers in prior artList_Preferr: Preferred list of biomarkersCorrelation: The correlation of the biomarker to sensitivity to thecompound

TABLE 1 Vincristine biomarkers List_2006 List_2005 List_PriorList_Preferr Correlation  [1,] UBB UBB 0.39  [2,] RPS4X RPS4X 0.34  [3,]S100A4 S100A4 0.32  [4,] NDUFS6 NDUFS6 0.31  [5,] B2M B2M 0.35  [6,]C14orf139 C14orf139 0.3  [7,] MAN1A1 MAN1A1 0.33  [8,] SLC25A5 SLC25A5SLC25A5 0.32  [9,] RPL10 RPL10 0.38 [10,] RPL12 RPL12 0.31 [11,] EIF5AEIF5A 0.31 [12,] RPL36A RPL36A RPL36A 0.3 [13,] SUI1 SUI1 0.33 [14,]BLMH BLMH 0.32 [15,] CTBP1 CTBP1 0.32 [16,] TBCA TBCA 0.3 [17,] MDH2MDH2 0.34 [18,] DXS9879E DXS9879E 0.35 [19,] SFRS3 [20,] CCT5 [21,]RPL39 [22,] UBE2S [23,] EEF1A1 [24,] COX7B [25,] RPLP2 [26,] RPL24 [27,]RPS23 [28,] RPL18 [29,] NCL [30,] RPL9 [31,] RPL10A [32,] RPS10 [33,]EIF3S2 [34,] SHFM1 [35,] RPS28 [36,] REA [37,] GAPD [38,] HNRPA1 [39,]RPS11 [40,] LDHB [41,] RPL3 [42,] RPL11 [43,] MRPL12 [44,] RPL18A [45,]RPS7

TABLE 2 Cisplatin biomarkers Cor- List_2006 List_2005 List_PriorList_Preferr relation  [1,] C1QR1 C1QR1 0.3  [2,] HCLS1 HCLS1 HCLS1 0.33 [3,] CD53 CD53 0.35  [4,] SLA SLA 0.37  [5,] PTPN7 PTPN7 PTPN7 0.31 [6,] PTPRCAP PTPRCAP 0.32  [7,] ZNFN1A1 ZNFN1A1 0.33  [8,] CENTB1CENTB1 0.37  [9,] PTPRC PTPRC 0.36 [10,] IFI16 IFI16 IFI16 0.31 [11,]ARHGEF6 ARHGEF6 0.35 [12,] SEC31L2 SEC31L2 0.32 [13,] CD3Z CD3Z 0.32[14,] GZMB GZMB 0.3 [15,] CD3D CD3D 0.34 [16,] MAP4K1 MAP4K1 0.32 [17,]GPR65 GPR65 0.39 [18,] PRF1 PRF1 0.31 [19,] ARHGAP15 ARHGAP15 0.35 [20,]TM6SF1 TM6SF1 0.41 [21,] TCF4 TCF4 0.4 [22,] GAPD [23,] ARHGDIB [24,]RPS27 [25,] C5orf13 [26,] LDHB [27,] SNRPF [28,] B2M [29,] FTL [30,] NCL[31,] MSN [32,] XPO1

TABLE 3 Azaguanine biomarkers List_2006 List_2005 List_PriorList_Preferr Correlation  [1,] MSN MSN MSN 0.36  [2,] SPARC SPARC SPARC0.48  [3,] VIM VIM VIM 0.47  [4,] SRM SRM SRM 0.32  [5,] SCARB1 SCARB10.4  [6,] SIAT1 SIAT1 0.31  [7,] CUGBP2 CUGBP2 0.37  [8,] GAS7 GAS7 0.34 [9,] ICAM1 ICAM1 0.43 [10,] WASPIP WASPIP 0.44 [11,] ITM2A ITM2A 0.31[12,] PALM2-AKAP2 PALM2-AKAP2 0.31 [13,] ANPEP ANPEP 0.33 [14,] PTPNS1PTPNS1 0.39 [15,] MPP1 MPP1 0.32 [16,] LNK LNK 0.43 [17,] FCGR2A FCGR2A0.3 [18,] EMP3 EMP3 EMP3 0.33 [19,] RUNX3 RUNX3 0.43 [20,] EVI2A EVI2A0.4 [21,] BTN3A3 BTN3A3 0.4 [22,] LCP2 LCP2 0.34 [23,] BCHE BCHE 0.35[24,] LY96 LY96 0.47 [25,] LCP1 LCP1 0.42 [26,] IFI16 IFI16 0.33 [27,]MCAM MCAM MCAM 0.37 [28,] MEF2C MEF2C 0.41 [29,] SLC1A4 SLC1A4 0.49[30,] BTN3A2 BTN3A2 0.43 [31,] FYN FYN 0.31 [32,] FN1 FN1 FN1 0.33 [33,]C1orf38 C1orf38 0.37 [34,] CHS1 CHS1 0.33 [35,] CAPN3 CAPN3 0.5 [36,]FCGR2C FCGR2C 0.34 [37,] TNIK TNIK 0.35 [38,] AMPD2 AMPD2 0.3 [39,]SEPT6 SEPT6 0.41 [40,] RAFTLIN RAFTLIN 0.39 [41,] SLC43A3 SLC43A3 0.52[42,] RAC2 RAC2 0.33 [43,] LPXN LPXN 0.54 [44,] CKIP-1 CKIP-1 0.33 [45,]FLJ10539 FLJ10539 0.33 [46,] FLJ35036 FLJ35036 0.36 [47,] DOCK10 DOCK100.3 [48,] TRPV2 TRPV2 0.31 [49,] IFRG28 IFRG28 0.3 [50,] LEF1 LEF1 0.31[51,] ADAMTS1 ADAMTS1 0.36 [52,] PRPS1 [53,] DDOST [54,] B2M [55,]LGALS1 [56,] CBFB [57,] SNRPB2 [58,] EIF2S2 [59,] HPRT1 [60,] FKBP1A[61,] GYPC [62,] UROD [63,] HNRPA1 [64,] SND1 [65,] COPA [66,] MAPRE1[67,] EIF3S2 [68,] ATP1B3 [69,] ECM1 [70,] ATOX1 [71,] NARS [72,] PGK1[73,] OK/SW-cl.56 [74,] EEF1A1 [75,] GNAI2 [76,] RPL7 [77,] PSMB9 [78,]GPNMB [79,] PPP1R11 [80,] MIA [81,] RAB7 [82,] SMS

TABLE 4 Etoposide biomarkers List_2006 List_2005 List_Prior List_PreferrCorrelation  [1,] CD99 CD99 CD99 0.3  [2,] INSIG1 INSIG1 0.35  [3,]LAPTM5 LAPTM5 0.32  [4,] PRG1 PRG1 0.34  [5,] MUF1 MUF1 0.35  [6,] HCLS1HCLS1 0.33  [7,] CD53 CD53 0.32  [8,] SLA SLA 0.37  [9,] SSBP2 SSBP20.37 [10,] GNB5 GNB5 0.35 [11,] MFNG MFNG 0.33 [12,] GMFG GMFG 0.32[13,] PSMB9 PSMB9 0.31 [14,] EVI2A EVI2A 0.41 [15,] PTPN7 PTPN7 0.3[16,] PTGER4 PTGER4 0.3 [17,] CXorf9 CXorf9 0.3 [18,] PTPRCAP PTPRCAP0.3 [19,] ZNFN1A1 ZNFN1A1 0.35 [20,] CENTB1 CENTB1 0.3 [21,] PTPRC PTPRC0.31 [22,] NAP1L1 NAP1L1 0.31 [23,] HLA-DRA HLA-DRA 0.34 [24,] IFI16IFI16 0.38 [25,] CORO1A CORO1A 0.3 [26,] ARHGEF6 ARHGEF6 0.33 [27,]PSCDBP PSCDBP 0.4 [28,] SELPLG SELPLG 0.35 [29,] LAT LAT 0.3 [30,]SEC31L2 SEC31L2 0.42 [31,] CD3Z CD3Z 0.36 [32,] SH2D1A SH2D1A 0.33 [33,]GZMB GZMB 0.34 [34,] SCN3A SCN3A 0.3 [35,] ITK ITK 0.35 [36,] RAFTLINRAFTLIN 0.39 [37,] DOCK2 DOCK2 0.33 [38,] CD3D CD3D 0.31 [39,] RAC2 RAC20.34 [40,] ZAP70 ZAP70 0.35 [41,] GPR65 GPR65 0.35 [42,] PRF1 PRF1 0.32[43,] ARHGAP15 ARHGAP15 0.32 [44,] NOTCH1 NOTCH1 0.31 [45,] UBASH3AUBASH3A 0.32 [46,] B2M [47,] MYC [48,] RPS24 [49,] PPIF [50,] PBEF1[51,] ANP32B

TABLE 5 Adriamycin biomarkers Cor- List_2006 List_2005 List_PriorList_Preferr relation  [1,] CD99 CD99 CD99 0.41  [2,] LAPTM5 LAPTM5 0.39 [3,] ALDOC ALDOC 0.31  [4,] HCLS1 HCLS1 0.32  [5,] CD53 CD53 0.31  [6,]SLA SLA 0.35  [7,] SSBP2 SSBP2 0.34  [8,] IL2RG IL2RG 0.38  [9,] GMFGGMFG 0.32 [10,] CXorf9 CXorf9 0.32 [11,] RHOH RHOH 0.31 [12,] PTPRCAPPTPRCAP 0.32 [13,] ZNFN1A1 ZNFN1A1 0.43 [14,] CENTB1 CENTB1 0.36 [15,]TCF7 TCF7 0.32 [16,] CD1C CD1C 0.3 [17,] MAP4K1 MAP4K1 0.35 [18,] CD1BCD1B 0.39 [19,] CD3G CD3G 0.31 [20,] PTPRC PTPRC 0.38 [21,] CCR9 CCR90.34 [22,] CORO1A CORO1A 0.38 [23,] CXCR4 CXCR4 0.3 [24,] ARHGEF6ARHGEF6 0.31 [25,] HEM1 HEM1 0.32 [26,] SELPLG SELPLG 0.31 [27,] LAT LAT0.31 [28,] SEC31L2 SEC31L2 0.33 [29,] CD3Z CD3Z 0.37 [30,] SH2D1A SH2D1A0.37 [31,] CD1A CD1A 0.4 [32,] LAIR1 LAIR1 0.39 [33,] ITK ITK 0.3 [34,]TRB@ TRB@ 0.34 [35,] CD3D CD3D 0.33 [36,] WBSCR20C WBSCR20C 0.34 [37,]ZAP70 ZAP70 0.33 [38,] IFI44 IFI44 0.32 [39,] GPR65 GPR65 0.31 [40,]AIF1 AIF1 0.3 [41,] ARHGAP15 ARHGAP15 0.37 [42,] NARF NARF 0.3 [43,]PACAP PACAP 0.32 [44,] KIAA0220 [45,] B2M [46,] TOP2A [47,] SNRPE [48,]RPS27 [49,] HNRPA1 [50,] CBX3 [51,] ANP32B [52,] DDX5 [53,] PPIA [54,]SNRPF [55,] USP7

TABLE 6 Aclarubicin biomarkers List_2006 List_2005 List_PriorList_Preferr Correlation  [1,] RPL12 RPL12 0.3  [2,] RPL32 RPL32 0.37 [3,] RPLP2 RPLP2 RPLP2 0.37  [4,] MYB MYB MYB 0.31  [5,] ZNFN1A1ZNFN1A1 0.34  [6,] SCAP1 SCAP1 0.33  [7,] STAT4 STAT4 0.31  [8,] SP140SP140 0.4  [9,] AMPD3 AMPD3 0.3 [10,] TNFAIP8 TNFAIP8 0.4 [11,] DDX18DDX18 0.31 [12,] TAF5 TAF5 0.3 [13,] FBL FBL 0.41 [14,] RPS2 RPS2 0.34[15,] PTPRC PTPRC 0.37 [16,] DOCK2 DOCK2 0.32 [17,] GPR65 GPR65 0.35[18,] HOXA9 HOXA9 0.33 [19,] FLJ12270 FLJ12270 0.31 [20,] HNRPD HNRPD0.4 [21,] LAMR1 [22,] RPS25 [23,] EIF5A [24,] TUFM [25,] HNRPA1 [26,]RPS9 [27,] ANP32B [28,] EIF4B [29,] HMGB2 [30,] RPS15A [31,] RPS7

TABLE 7 Mitoxantrone biomarkers Cor- List_2006 List_2005 List_PriorList_Preferr relation  [1,] PGAM1 PGAM1 0.32  [2,] DPYSL3 DPYSL3 0.36 [3,] INSIG1 INSIG1 0.32  [4,] GJA1 GJA1 0.31  [5,] BNIP3 BNIP3 0.31 [6,] PRG1 PRG1 PRG1 0.39  [7,] G6PD G6PD G6PD 0.34  [8,] BASP1 BASP10.31  [9,] PLOD2 PLOD2 0.34 [10,] LOXL2 LOXL2 0.31 [11,] SSBP2 SSBP20.36 [12,] C1orf29 C1orf29 0.35 [13,] TOX TOX 0.35 [14,] STC1 STC1 0.39[15,] TNFRSF1A TNFRSF1A TNFRSF1A 0.34 [16,] NCOR2 NCOR2 NCOR2 0.3 [17,]NAP1L1 NAP1L1 NAP1L1 0.32 [18,] LOC94105 LOC94105 0.34 [19,] COL6A2COL6A2 0.3 [20,] ARHGEF6 ARHGEF6 ARHGEF6 0.34 [21,] GATA3 GATA3 0.35[22,] TFPI TFPI 0.31 [23,] LAT LAT 0.31 [24,] CD3Z CD3Z 0.37 [25,] AF1QAF1Q 0.33 [26,] MAP1B MAP1B MAP1B 0.34 [27,] PTPRC PTPRC 0.31 [28,]PRKCA PRKCA 0.35 [29,] TRIM22 TRIM22 0.3 [30,] CD3D CD3D 0.31 [31,]BCAT1 BCAT1 0.32 [32,] IFI44 IFI44 0.33 [33,] CCL2 CCL2 0.37 [34,] RAB31RAB31 0.31 [35,] CUTC CUTC 0.33 [36,] NAP1L2 NAP1L2 0.33 [37,] NME7 NME70.35 [38,] FLJ21159 FLJ21159 0.33 [39,] COL5A2 COL5A2 0.38 [40,] B2M[41,] OK/SW-cl.56 [42,] TOP2A [43,] ELA2B [44,] PTMA [45,] LMNB1 [46,]HNRPA1 [47,] RPL9 [48,] C5orf13 [49,] ANP32B [50,] TUBA3 [51,] HMGN2[52,] PRPS1 [53,] DDX5 [54,] PPIA [55,] PSMB9 [56,] SNRPF

TABLE 8 Mitomycin biomarkers List_2006 HU6800 List_Prior List_PreferrCorrelation [1,] STC1 STC1 0.34 [2,] GPR65 GPR65 0.32 [3,] DOCK10 DOCK100.35 [4,] COL5A2 COL5A2 0.33 [5,] FAM46A FAM46A 0.36 [6,] LOC54103LOC54103 0.39

TABLE 9 Paclitaxel (Taxol) biomarkers List_2006 HU6800 List_PriorList_Preferr Correlation  [1,] RPL10 RPL10 0.31  [2,] RPS4X RPS4X 0.31 [3,] NUDC NUDC 0.3  [4,] RALY RALY 0.31  [5,] DKC1 DKC1 0.3  [6,]DKFZP564C186 DKFZP564C186 0.32  [7,] PRP19 PRP19 0.31  [8,] RAB9P40RAB9P40 0.33  [9,] HSA9761 HSA9761 0.37 [10,] GMDS GMDS 0.3 [11,] CEP1CEP1 0.3 [12,] IL13RA2 IL13RA2 0.34 [13,] MAGEB2 MAGEB2 0.41 [14,] HMGN2HMGN2 0.35 [15,] ALMS1 ALMS1 0.3 [16,] GPR65 GPR65 0.31 [17,] FLJ10774FLJ10774 0.31 [18,] NOL8 NOL8 0.31 [19,] DAZAP1 DAZAP1 0.32 [20,]SLC25A15 SLC25A15 0.31 [21,] PAF53 PAF53 0.36 [22,] DXS9879E DXS9879E0.31 [23,] PITPNC1 PITPNC1 0.33 [24,] SPANXC SPANXC 0.3 [25,] KIAA1393KIAA1393 0.33

TABLE 10 Gemcitabine (Gemzar) biomarkers List_2006 HU6800 List_PriorList_Preferr Correlation  [1,] PFN1 PFN1 0.37  [2,] PGAM1 PGAM1 0.35 [3,] K-ALPHA-1 K-ALPHA-1 0.34  [4,] CSDA CSDA 0.31  [5,] UCHL1 UCHL10.36  [6,] PWP1 PWP1 0.37  [7,] PALM2- PALM2- 0.31 AKAP2 AKAP2  [8,]TNFRSF1A TNFRSF1A 0.31  [9,] ATP5G2 ATP5G2 0.36 [10,] AF1Q AF1Q 0.31[11,] NME4 NME4 0.31 [12,] FHOD1 FHOD1 0.32

TABLE 11 Taxotere (docetaxel) biomarkers List_2006 List_2005 List_PriorList_Preferr Correlation  [1,] ANP32B ANP32B 0.45  [2,] GTF3A GTF3A 0.31 [3,] RRM2 RRM2 0.31  [4,] TRIM14 TRIM14 0.31  [5,] SKP2 SKP2 0.33  [6,]TRIP13 TRIP13 0.36  [7,] RFC3 RFC3 0.45  [8,] CASP7 CASP7 0.32  [9,] TXNTXN 0.36 [10,] MCM5 MCM5 0.34 [11,] PTGES2 PTGES2 0.39 [12,] OBFC1 OBFC10.37 [13,] EPB41L4B EPB41L4B 0.32 [14,] CALML4 CALML4 0.31

TABLE 12 Dexamethasone biomarkers Cor- List_2006 HU6800 List_PriorList_Preferr relation  [1,] IFITM2 IFITM2 0.38  [2,] UBE2L6 UBE2L6 0.32 [3,] LAPTM5 LAPTM5 LAPTM5 0.36  [4,] USP4 USP4 0.33  [5,] ITM2A ITM2A0.38  [6,] ITGB2 ITGB2 0.42  [7,] ANPEP ANPEP 0.31  [8,] CD53 CD53 0.34 [9,] IL2RG IL2RG IL2RG 0.36 [10,] CD37 CD37 0.34 [11,] GPRASP1 GPRASP10.36 [12,] PTPN7 PTPN7 0.31 [13,] CXorf9 CXorf9 0.36 [14,] RHOH RHOHRHOH 0.33 [15,] GIT2 GIT2 0.31 [16,] ADORA2A ADORA2A 0.31 [17,] ZNFN1A1ZNFN1A1 0.35 [18,] GNA15 GNA15 GNA15 0.33 [19,] CEP1 CEP1 0.31 [20,]TNFRSF7 TNFRSF7 0.46 [21,] MAP4K1 MAP4K1 0.3 [22,] CCR7 CCR7 0.33 [23,]CD3G CD3G 0.35 [24,] PTPRC PTPRC 0.41 [25,] ATP2A3 ATP2A3 ATP2A3 0.4[26,] UCP2 UCP2 0.3 [27,] CORO1A CORO1A CORO1A 0.39 [28,] GATA3 GATA3GATA3 0.37 [29,] CDKN2A CDKN2A 0.32 [30,] HEM1 HEM1 0.3 [31,] TARP TARP0.3 [32,] LAIR1 LAIR1 0.34 [33,] SH2D1A SH2D1A 0.34 [34,] FLII FLII FLII0.33 [35,] SEPT6 SEPT6 0.34 [36,] HA-1 HA-1 0.34 [37,] CREB3L1 CREB3L10.31 [38,] ERCC2 ERCC2 0.65 [39,] CD3D CD3D CD3D 0.32 [40,] LST1 LST10.39 [41,] AIF1 AIF1 0.35 [42,] ADA ADA 0.33 [43,] DATF1 DATF1 0.41[44,] ARHGAP15 ARHGAP15 0.3 [45,] PLAC8 PLAC8 0.31 [46,] CECR1 CECR10.31 [47,] LOC81558 LOC81558 0.33 [48,] EHD2 EHD2 0.37

TABLE 13 Ara-C (Cytarabine hydrochloride) biomarkers List_2006 HU6800List_Prior List_Preferr Correlation  [1,] ITM2A ITM2A 0.32  [2,] RHOHRHOH 0.31  [3,] PRIM1 PRIM1 0.3  [4,] CENTB1 CENTB1 0.31  [5,] GNA15GNA15 0.32  [6,] NAP1L1 NAP1L1 NAP1L1 0.31  [7,] ATP5G2 ATP5G2 0.31 [8,] GATA3 GATA3 0.33  [9,] PRKCQ PRKCQ 0.32 [10,] SH2D1A SH2D1A 0.3[11,] SEPT6 SEPT6 0.42 [12,] PTPRC PTPRC 0.35 [13,] NME4 NME4 0.33 [14,]RPL13 RPL13 0.3 [15,] CD3D CD3D 0.31 [16,] CD1E CD1E 0.32 [17,] ADA ADAADA 0.34 [18,] FHOD1 FHOD1 0.31

TABLE 14 Methylprednisolone biomarkers Cor- List_2006 HU6800 List_PriorList_Preferr relation  [1,] CD99 CD99 CD99 0.31  [2,] SRRM1 SRRM1 0.31 [3,] ARHGDIB ARHGDIB ARHGDIB 0.31  [4,] LAPTM5 LAPTM5 LAPTM5 0.37  [5,]VWF VWF 0.45  [6,] ITM2A ITM2A 0.35  [7,] ITGB2 ITGB2 ITGB2 0.43  [8,]LGALS9 LGALS9 LGALS9 0.43  [9,] INPP5D INPP5D 0.34 [10,] SATB1 SATB1SATB1 0.32 [11,] CD53 CD53 CD53 0.33 [12,] TFDP2 TFDP2 TFDP2 0.4 [13,]SLA SLA SLA 0.31 [14,] IL2RG IL2RG IL2RG 0.3 [15,] MFNG MFNG 0.3 [16,]CD37 CD37 0.37 [17,] GMFG GMFG 0.4 [18,] SELL SELL 0.33 [19,] CDW52CDW52 CDW52 0.33 [20,] LRMP LRMP 0.32 [21,] ICAM2 ICAM2 0.38 [22,] RIMS3RIMS3 0.36 [23,] PTPN7 PTPN7 PTPN7 0.39 [24,] ARHGAP25 ARHGAP25 0.37[25,] LCK LCK LCK 0.3 [26,] CXorf9 CXorf9 0.3 [27,] RHOH RHOH RHOH 0.51[28,] PTPRCAP PTPRCAP PTPRCAP 0.5 [29,] GIT2 GIT2 0.33 [30,] ZNFN1A1ZNFN1A1 ZNFN1A1 0.53 [31,] CENTB1 CENTB1 CENTB1 0.36 [32,] LCP2 LCP20.34 [33,] SPI1 SPI1 0.3 [34,] GNA15 GNA15 GNA15 0.39 [35,] GZMA GZMA0.31 [36,] CEP1 CEP1 0.37 [37,] BLM BLM 0.33 [38,] CD8A CD8A 0.38 [39,]SCAP1 SCAP1 0.32 [40,] CD2 CD2 0.48 [41,] CD1C CD1C CD1C 0.37 [42,]TNFRSF7 TNFRSF7 0.31 [43,] VAV1 VAV1 0.41 [44,] MAP4K1 MAP4K1 MAP4K10.36 [45,] CCR7 CCR7 0.37 [46,] C6orf32 C6orf32 0.38 [47,] ALOX15BALOX15B 0.43 [48,] BRDT BRDT 0.33 [49,] CD3G CD3G CD3G 0.51 [50,] PTPRCPTPRC 0.37 [51,] LTB LTB 0.32 [52,] ATP2A3 ATP2A3 ATP2A3 0.3 [53,] NVLNVL 0.31 [54,] RASGRP2 RASGRP2 0.35 [55,] LCP1 LCP1 LCP1 0.34 [56,]CORO1A CORO1A CORO1A 0.41 [57,] CXCR4 CXCR4 CXCR4 0.3 [58,] PRKD2 PRKD20.33 [59,] GATA3 GATA3 GATA3 0.39 [60,] TRA@ TRA@ 0.4 [61,] PRKCB1PRKCB1 PRKCB1 0.35 [62,] HEM1 HEM1 0.32 [63,] KIAA0922 KIAA0922 0.36[64,] TARP TARP 0.49 [65,] SEC31L2 SEC31L2 0.32 [66,] PRKCQ PRKCQ 0.37[67,] SH2D1A SH2D1A 0.33 [68,] CHRNA3 CHRNA3 0.5 [69,] CD1A CD1A 0.44[70,] LST1 LST1 0.36 [71,] LAIR1 LAIR1 0.47 [72,] CACNA1G CACNA1G 0.33[73,] TRB@ TRB@ TRB@ 0.31 [74,] SEPT6 SEPT6 SEPT6 0.33 [75,] HA-1 HA-10.42 [76,] DOCK2 DOCK2 0.32 [77,] CD3D CD3D CD3D 0.41 [78,] TRD@ TRD@0.38 [79,] T3JAM T3JAM 0.37 [80,] FNBP1 FNBP1 0.37 [81,] CD6 CD6 0.4[82,] AIF1 AIF1 AIF1 0.31 [83,] FOLH1 FOLH1 0.45 [84,] CD1E CD1E CD1E0.58 [85,] LY9 LY9 0.39 [86,] UGT2B17 UGT2B17 0.47 [87,] ADA ADA ADA0.39 [88,] CDKL5 CDKL5 0.44 [89,] TRIM TRIM 0.38 [90,] EVL EVL 0.39[91,] DATF1 DATF1 0.31 [92,] RGC32 RGC32 0.51 [93,] PRKCH PRKCH 0.3[94,] ARHGAP15 ARHGAP15 0.34 [95,] NOTCH1 NOTCH1 0.36 [96,] BIN2 BIN20.31 [97,] SEMA4G SEMA4G 0.35 [98,] DPEP2 DPEP2 0.33 [99,] CECR1 CECR10.36 [100,]  BCL11B BCL11B 0.33 [101,]  STAG3 STAG3 0.41 [102,]  GALNT6GALNT6 0.32 [103,]  UBASH3A UBASH3A 0.3 [104,]  PHEMX PHEMX 0.38 [105,] FLJ13373 FLJ13373 0.34 [106,]  LEF1 LEF1 0.49 [107,]  IL21R IL21R 0.42[108,]  MGC17330 MGC17330 0.33 [109,]  AKAP13 AKAP13 0.53 [110,]  ZNF335ZNF335 0.3 [111,]  GIMAP5 GIMAP5 0.34

TABLE 15 Methotrexate biomarkers List_2006 HU6800 List_PriorList_Preferr Correlation  [1,] PRPF8 PRPF8 0.34  [2,] RPL18 RPL18 0.34 [3,] RNPS1 RNPS1 0.36  [4,] RPL32 RPL32 0.39  [5,] EEF1G EEF1G 0.34 [6,] GOT2 GOT2 0.31  [7,] RPL13A RPL13A 0.31  [8,] PTMA PTMA PTMA 0.41 [9,] RPS15 RPS15 0.39 [10,] RPLP2 RPLP2 RPLP2 0.32 [11,] CSDA CSDA 0.39[12,] KHDRBS1 KHDRBS1 0.32 [13,] SNRPA SNRPA 0.31 [14,] IMPDH2 IMPDH2IMPDH2 0.39 [15,] RPS19 RPS19 0.47 [16,] NUP88 NUP88 0.36 [17,] ATP5DATP5D 0.33 [18,] PCBP2 PCBP2 0.32 [19,] ZNF593 ZNF593 0.4 [20,] HSU79274HSU79274 0.32 [21,] PRIM1 PRIM1 0.3 [22,] PFDN5 PFDN5 0.33 [23,] OXA1LOXA1L 0.37 [24,] H3F3A H3F3A 0.42 [25,] ATIC ATIC 0.31 [26,] RPL13 RPL130.36 [27,] CIAPIN1 CIAPIN1 0.34 [28,] FBL FBL 0.33 [29,] RPS2 RPS2 RPS20.32 [30,] PCCB PCCB 0.36 [31,] RBMX RBMX 0.33 [32,] SHMT2 SHMT2 0.34[33,] RPLP0 RPLP0 0.35 [34,] HNRPA1 HNRPA1 HNRPA1 0.35 [35,] STOML2STOML2 0.32 [36,] RPS9 RPS9 0.36 [37,] SKB1 SKB1 0.33 [38,] GLTSCR2GLTSCR2 0.37 [39,] CCNB1IP1 CCNB1IP1 0.3 [40,] MRPS2 MRPS2 0.33 [41,]FLJ20859 FLJ20859 0.34 [42,] FLJ12270 FLJ12270 0.3

TABLE 16 Bleomycin biomarkers List_2006 HU6800 List_Prior List_PreferrCorrelation  [1,] MSN MSN 0.3  [2,] PFN1 PFN1 0.45  [3,] HK1 HK1 0.33 [4,] ACTR2 ACTR2 0.31  [5,] MCL1 MCL1 0.31  [6,] ZYX ZYX 0.32  [7,]RAP1B RAP1B 0.34  [8,] GNB2 GNB2 0.32  [9,] EPAS1 EPAS1 0.31 [10,] PGAM1PGAM1 0.42 [11,] CKAP4 CKAP4 0.31 [12,] DUSP1 DUSP1 0.4 [13,] MYL9 MYL90.4 [14,] K-ALPHA-1 K-ALPHA-1 0.37 [15,] LGALS1 LGALS1 0.38 [16,] CSDACSDA CSDA 0.3 [17,] AKR1B1 AKR1B1 0.32 [18,] IFITM2 IFITM2 IFITM2 0.36[19,] ITGA5 ITGA5 0.43 [20,] VIM VIM 0.39 [21,] DPYSL3 DPYSL3 0.44 [22,]JUNB JUNB 0.32 [23,] ITGA3 ITGA3 0.38 [24,] NFKBIA NFKBIA 0.32 [25,]LAMB1 LAMB1 0.37 [26,] FHL1 FHL1 0.31 [27,] INSIG1 INSIG1 0.31 [28,]TIMP1 TIMP1 0.48 [29,] GJA1 GJA1 0.54 [30,] PSME2 PSME2 0.34 [31,] PRG1PRG1 0.46 [32,] EXT1 EXT1 0.35 [33,] DKFZP434J154 DKFZP434J154 0.31[34,] OPTN OPTN 0.31 [35,] M6PRBP1 M6PRBP1 0.52 [36,] MVP MVP 0.34 [37,]VASP VASP 0.31 [38,] ARL7 ARL7 0.39 [39,] NNMT NNMT NNMT 0.34 [40,] TAP1TAP1 0.3 [41,] COL1A1 COL1A1 COL1A1 0.33 [42,] BASP1 BASP1 0.35 [43,]PLOD2 PLOD2 0.37 [44,] ATF3 ATF3 0.42 [45,] PALM2-AKAP2 PALM2-AKAP2 0.33[46,] IL8 IL8 0.34 [47,] ANPEP ANPEP 0.35 [48,] LOXL2 LOXL2 0.32 [49,]TGFB1 TGFB1 0.31 [50,] IL4R IL4R 0.31 [51,] DGKA DGKA 0.32 [52,] STC2STC2 0.31 [53,] SEC61G SEC61G 0.41 [54,] NFIL3 NFIL3 NFIL3 0.47 [55,]RGS3 RGS3 0.37 [56,] NK4 NK4 0.34 [57,] F2R F2R 0.34 [58,] TPM2 TPM20.35 [59,] PSMB9 PSMB9 PSMB9 0.34 [60,] LOX LOX 0.37 [61,] STC1 STC10.35 [62,] CSPG2 CSPG2 CSPG2 0.35 [63,] PTGER4 PTGER4 0.31 [64,] IL6 IL60.34 [65,] SMAD3 SMAD3 0.38 [66,] PLAU PLAU PLAU 0.35 [67,] WNT5A WNT5A0.44 [68,] BDNF BDNF 0.34 [69,] TNFRSF1A TNFRSF1A TNFRSF1A 0.46 [70,]FLNC FLNC 0.34 [71,] DKFZP564K0822 DKFZP564K0822 0.34 [72,] FLOT1 FLOT10.38 [73,] PTRF PTRF 0.39 [74,] HLA-B HLA-B 0.36 [75,] COL6A2 COL6A2COL6A2 0.32 [76,] MGC4083 MGC4083 0.32 [77,] TNFRSF10B TNFRSF10B 0.34[78,] PLAGL1 PLAGL1 0.31 [79,] PNMA2 PNMA2 0.38 [80,] TFPI TFPI 0.38[81,] LAT LAT 0.46 [82,] GZMB GZMB 0.51 [83,] CYR61 CYR61 0.37 [84,]PLAUR PLAUR PLAUR 0.35 [85,] FSCN1 FSCN1 FSCN1 0.32 [86,] ERP70 ERP700.32 [87,] AF1Q AF1Q 0.3 [88,] UBC UBC 0.37 [89,] FGFR1 FGFR1 0.33 [90,]HIC HIC 0.33 [91,] BAX BAX 0.35 [92,] COL4A2 COL4A2 COL4A2 0.32 [93,]COL6A1 COL6A1 0.32 [94,] IFITM3 IFITM3 0.3 [95,] MAP1B MAP1B 0.38 [96,]FLJ46603 FLJ46603 0.37 [97,] RAFTLIN RAFTLIN 0.34 [98,] RRAS RRAS 0.31[99,] FTL FTL 0.3 [100,]  KIAA0877 KIAA0877 0.31 [101,]  MT1E MT1E MT1E0.31 [102,]  CDC10 CDC10 0.51 [103,]  DOCK2 DOCK2 0.32 [104,]  TRIM22TRIM22 0.36 [105,]  RIS1 RIS1 0.37 [106,]  BCAT1 BCAT1 0.42 [107,]  PRF1PRF1 0.34 [108,]  DBN1 DBN1 0.36 [109,]  MT1K MT1K 0.3 [110,]  TMSB10TMSB10 0.42 [111,]  RAB31 RAB31 0.45 [112,]  FLJ10350 FLJ10350 0.4[113,]  C1orf24 C1orf24 0.34 [114,]  NME7 NME7 0.46 [115,]  TMEM22TMEM22 0.3 [116,]  TPK1 TPK1 0.37 [117,]  COL5A2 COL5A2 0.34 [118,] ELK3 ELK3 0.38 [119,]  CYLD CYLD 0.4 [120,]  ADAMTS1 ADAMTS1 0.31[121,]  EHD2 EHD2 0.41 [122,]  ACTB ACTB ACTB 0.33

TABLE 17 Methyl-GAG (Methyl glyoxal bis(amidinohydrazone)dihydrochloride) List_2006 HU6800 List_Prior List_Preferr Correlation [1,] PTMA PTMA 0.32  [2,] SSRP1 SSRP1 0.37  [3,] NUDC NUDC 0.35  [4,]CTSC CTSC 0.35  [5,] AP1G2 AP1G2 0.33  [6,] PSME2 PSME2 0.3  [7,] LBRLBR 0.38  [8,] EFNB2 EFNB2 0.31  [9,] SERPINA1 SERPINA1 0.34 [10,]SSSCA1 SSSCA1 0.32 [11,] EZH2 EZH2 0.36 [12,] MYB MYB MYB 0.33 [13,]PRIM1 PRIM1 0.39 [14,] H2AFX H2AFX 0.33 [15,] HMGA1 HMGA1 0.35 [16,]HMMR HMMR 0.33 [17,] TK2 TK2 0.42 [18,] WHSC1 WHSC1 0.35 [19,] DIAPH1DIAPH1 0.34 [20,] LAMB3 LAMB3 0.31 [21,] DPAGT1 DPAGT1 0.42 [22,] UCK2UCK2 0.31 [23,] SERPINB1 SERPINB1 0.31 [24,] MDN1 MDN1 0.35 [25,] BRRN1BRRN1 0.33 [26,] G0S2 G0S2 0.43 [27,] RAC2 RAC2 0.35 [28,] MGC21654MGC21654 0.36 [29,] GTSE1 GTSE1 0.35 [30,] TACC3 TACC3 0.31 [31,] PLEK2PLEK2 0.32 [32,] PLAC8 PLAC8 0.31 [33,] HNRPD HNRPD 0.35 [34,] PNAS-4PNAS-4 0.3

TABLE 18 Carboplatin biomarkers List_2006 HU6800 List_Prior List_PreferrCorrelation  [1,] MSN MSN 0.31  [2,] ITGA5 ITGA5 0.43  [3,] VIM VIM 0.34 [4,] TNFAIP3 TNFAIP3 0.4  [5,] CSPG2 CSPG2 0.35  [6,] WNT5A WNT5A 0.34 [7,] FOXF2 FOXF2 0.36  [8,] LOC94105 LOC94105 0.32  [9,] IFI16 IFI160.38 [10,] LRRN3 LRRN3 0.33 [11,] FGFR1 FGFR1 0.37 [12,] DOCK10 DOCK100.4 [13,] LEPRE1 LEPRE1 0.32 [14,] COL5A2 COL5A2 0.3 [15,] ADAMTS1ADAMTS1 0.34

TABLE 19 5-FU (5-Fluorouracil) biomarkers List_2006 HU6800 List_PriorList_Preferr Correlation  [1,] RPL18 RPL18 0.39  [2,] RPL10A RPL10A 0.36 [3,] RNPS1 RNPS1 0.3  [4,] ANAPC5 ANAPC5 0.5  [5,] EEF1B2 EEF1B2 0.4 [6,] RPL13A RPL13A 0.38  [7,] RPS15 RPS15 0.34  [8,] AKAP1 AKAP1 0.37 [9,] NDUFAB1 NDUFAB1 0.3 [10,] APRT APRT 0.32 [11,] ZNF593 ZNF593 0.37[12,] MRP63 MRP63 0.31 [13,] IL6R IL6R 0.31 [14,] RPL13 RPL13 0.31 [15,]SART3 SART3 0.35 [16,] RPS6 RPS6 0.49 [17,] UCK2 UCK2 0.38 [18,] RPL3RPL3 0.32 [19,] RPL17 RPL17 0.34 [20,] RPS2 RPS2 0.32 [21,] PCCB PCCB0.31 [22,] TOMM20 TOMM20 0.39 [23,] SHMT2 SHMT2 0.36 [24,] RPLP0 RPLP00.3 [25,] GTF3A GTF3A 0.5 [26,] STOML2 STOML2 0.4 [27,] DKFZp564J157DKFZp564J157 0.38 [28,] MRPS2 MRPS2 0.34 [29,] ALG5 ALG5 0.37 [30,]CALML4 CALML4 0.3

TABLE 20 Rituximab (e.g., Mabthera) biomarkers List_2006 List_PriorList_Preferr Correlation  [1,] ITK ITK 0.36  [2,] KIFC1 KIFC1 0.36  [3,]VLDLR VLDLR 0.39  [4,] RUNX1 RUNX1 0.32  [5,] PAFAH1B3 PAFAH1B3 0.32 [6,] H1FX H1FX 0.43  [7,] RNF144 RNF144 0.38  [8,] TMSNB TMSNB 0.47 [9,] CRY1 CRY1 0.37 [10,] MAZ MAZ 0.33 [11,] SLA SLA 0.35 [12,] SRF SRF0.37 [13,] UMPS UMPS 0.41 [14,] CD3Z CD3Z 0.33 [15,] PRKCQ PRKCQ 0.31[16,] HNRPM HNRPM 0.45 [17,] ZAP70 ZAP70 0.38 [18,] ADD1 ADD1 0.31 [19,]RFC5 RFC5 0.35 [20,] TM4SF2 TM4SF2 0.33 [21,] PFN2 PFN2 0.3 [22,] BMI1BMI1 0.31 [23,] TUBGCP3 TUBGCP3 0.33 [24,] ATP6V1B2 ATP6V1B2 0.42 [25,]RALY RALY 0.31 [26,] PSMC5 PSMC5 0.36 [27,] CD1D CD1D 0.32 [28,] ADA ADA0.34 [29,] CD99 CD99 0.33 [30,] CD2 CD2 0.43 [31,] CNP CNP 0.48 [32,]ERG ERG 0.47 [33,] MYL6 MYL6 0.41 [34,] CD3E CD3E 0.36 [35,] CD1A CD1A0.46 [36,] CD1B CD1B 0.47 [37,] STMN1 STMN1 0.32 [38,] PSMC3 PSMC3 0.38[39,] RPS4Y1 RPS4Y1 0.36 [40,] AKT1 AKT1 0.38 [41,] TAL1 TAL1 0.37 [42,]GNA15 GNA15 0.37 [43,] UBE2A UBE2A 0.35 [44,] TCF12 TCF12 0.35 [45,]UBE2S UBE2S 0.52 [46,] CCND3 CCND3 0.38 [47,] PAX6 PAX6 0.35 [48,] MDKMDK 0.3 [49,] CAPG CAPG 0.36 [50,] RAG2 RAG2 0.39 [51,] ACTN1 ACTN1 0.37[52,] GSTM2 GSTM2 0.47 [53,] SATB1 SATB1 0.36 [54,] NASP NASP 0.3 [55,]IGFBP2 IGFBP2 0.46 [56,] CDH2 CDH2 0.49 [57,] CRABP1 CRABP1 0.36 [58,]DBN1 DBN1 0.49 [59,] CTNNA1 CTNNA1 0.53 [60,] AKR1C1 AKR1C1 0.32 [61,]CACNB3 CACNB3 0.37 [62,] FARSLA FARSLA 0.35 [63,] CASP2 CASP2 0.42 [64,]CASP2 CASP2 0.31 [65,] E2F4 E2F4 0.36 [66,] LCP2 LCP2 0.35 [67,] CASP6CASP6 0.32 [68,] MYB MYB 0.3 [69,] SFRS6 SFRS6 0.44 [70,] GLRB GLRB 0.34[71,] NDN NDN 0.39 [72,] CPSF1 CPSF1 0.33 [73,] GNAQ GNAQ 0.44 [74,]TUSC3 TUSC3 0.41 [75,] GNAQ GNAQ 0.54 [76,] JARID2 JARID2 0.44 [77,]OCRL OCRL 0.5 [78,] FHL1 FHL1 0.36 [79,] EZH2 EZH2 0.4 [80,] SMOX SMOX0.35 [81,] SLC4A2 SLC4A2 0.35 [82,] UFD1L UFD1L 0.3 [83,] SEPW1 SEPW10.31 [84,] ZNF32 ZNF32 0.35 [85,] HTATSF1 HTATSF1 0.35 [86,] SHD1 SHD10.43 [87,] PTOV1 PTOV1 0.42 [88,] NXF1 NXF1 0.46 [89,] FYB FYB 0.47[90,] TRIM28 TRIM28 0.38 [91,] BC008967 BC008967 0.4 [92,] TRB@ TRB@ 0.3[93,] TFRC TFRC 0.31 [94,] H1F0 H1F0 0.36 [95,] CD3D CD3D 0.32 [96,]CD3G CD3G 0.4 [97,] CENPB CENPB 0.36 [98,] ALDH2 ALDH2 0.33 [99,] ANXA1ANXA1 0.35 [100,]  H2AFX H2AFX 0.51 [101,]  CD1E CD1E 0.33 [102,]  DDX5DDX5 0.39 [103,]  ABL1 ABL1 0.3 [104,]  CCNA2 CCNA2 0.3 [105,]  ENO2ENO2 0.35 [106,]  SNRPB SNRPB 0.38 [107,]  GATA3 GATA3 0.36 [108,]  RRM2RRM2 0.48 [109,]  GLUL GLUL 0.4 [110,]  TCF7 TCF7 0.39 [111,]  FGFR1FGFR1 0.33 [112,]  SOX4 SOX4 0.3 [113,]  MAL MAL 0.3 [114,]  NUCB2 NUCB20.38 [115,]  SMA3 SMA3 0.31 [116,]  FAT FAT 0.52 [117,]  UNG UNG 0.31[118,]  ARHGDIB ARHGDIB 0.36 [119,]  RUNX1 RUNX1 0.38 [120,]  MPHOSPH6MPHOSPH6 0.5 [121,]  DCTN1 DCTN1 0.34 [122,]  SH3GL3 SH3GL3 0.38 [123,] VIM VIM 0.41 [124,]  PLEKHC1 PLEKHC1 0.3 [125,]  CD47 CD47 0.32 [126,] POLR2F POLR2F 0.37 [127,]  RHOH RHOH 0.43 [128,]  ADD1 ADD1 0.46 [129,] ATP2A3 ATP2A3 0.38

TABLE 21 Radiation sensitivity biomarkers List_2006 HU6800 List_PriorList_Preferr Correlation  [1,] TRA1 TRA1 0.36  [2,] ACTN4 ACTN4 0.36 [3,] WARS WARS 0.39  [4,] CALM1 CALM1 0.32  [5,] CD63 CD63 CD63 0.32 [6,] CD81 CD81 0.43  [7,] FKBP1A FKBP1A 0.38  [8,] CALU CALU 0.47  [9,]IQGAP1 IQGAP1 0.37 [10,] CTSB CTSB 0.33 [11,] MGC8721 MGC8721 0.35 [12,]STAT1 STAT1 0.37 [13,] TACC1 TACC1 0.41 [14,] TM4SF8 TM4SF8 0.33 [15,]CD59 CD59 0.31 [16,] CKAP4 CKAP4 CKAP4 0.45 [17,] DUSP1 DUSP1 DUSP1 0.38[18,] RCN1 RCN1 0.31 [19,] MGC8902 MGC8902 0.35 [20,] LGALS1 LGALS1LGALS1 0.33 [21,] BHLHB2 BHLHB2 0.3 [22,] RRBP1 RRBP1 0.31 [23,] PKM2PKM2 0.33 [24,] PRNP PRNP 0.42 [25,] PPP2CB PPP2CB 0.31 [26,] CNN3 CNN30.36 [27,] ANXA2 ANXA2 ANXA2 0.32 [28,] IER3 IER3 0.34 [29,] JAK1 JAK10.33 [30,] MARCKS MARCKS 0.43 [31,] LUM LUM 0.48 [32,] FER1L3 FER1L30.47 [33,] SLC20A1 SLC20A1 0.41 [34,] EIF4G3 EIF4G3 0.36 [35,] HEXB HEXB0.46 [36,] EXT1 EXT1 0.47 [37,] TJP1 TJP1 0.32 [38,] CTSL CTSL CTSL 0.38[39,] SLC39A6 SLC39A6 0.36 [40,] RIOK3 RIOK3 0.38 [41,] CRK CRK 0.37[42,] NNMT NNMT 0.37 [43,] COL1A1 COL1A1 0.35 [44,] TRAM2 TRAM2 TRAM20.35 [45,] ADAM9 ADAM9 0.52 [46,] DNAJC7 DNAJC7 0.38 [47,] PLSCR1 PLSCR10.35 [48,] PRSS23 PRSS23 0.3 [49,] PLOD2 PLOD2 0.36 [50,] NPC1 NPC1 0.39[51,] TOB1 TOB1 0.37 [52,] GFPT1 GFPT1 0.47 [53,] IL8 IL8 0.36 [54,]DYRK2 DYRK2 0.3 [55,] PYGL PYGL 0.46 [56,] LOXL2 LOXL2 0.49 [57,]KIAA0355 KIAA0355 0.36 [58,] UGDH UGDH 0.49 [59,] NFIL3 NFIL3 0.53 [60,]PURA PURA 0.32 [61,] ULK2 ULK2 0.37 [62,] CENTG2 CENTG2 0.35 [63,] NID2NID2 0.42 [64,] CAP350 CAP350 0.31 [65,] CXCL1 CXCL1 0.36 [66,] BTN3A3BTN3A3 0.35 [67,] IL6 IL6 0.32 [68,] WNT5A WNT5A 0.3 [69,] FOXF2 FOXF20.44 [70,] LPHN2 LPHN2 0.34 [71,] CDH11 CDH11 0.39 [72,] P4HA1 P4HA10.33 [73,] GRP58 GRP58 0.44 [74,] ACTN1 ACTN1 ACTN1 0.41 [75,] CAPN2CAPN2 0.54 [76,] DSIPI DSIPI 0.44 [77,] MAP1LC3B MAP1LC3B 0.5 [78,]GALIG GALIG GALIG 0.36 [79,] IGSF4 IGSF4 0.4 [80,] IRS2 IRS2 0.35 [81,]ATP2A2 ATP2A2 0.35 [82,] OGT OGT 0.3 [83,] TNFRSF10B TNFRSF10B 0.31[84,] KIAA1128 KIAA1128 0.35 [85,] TM4SF1 TM4SF1 0.35 [86,] RBPMS RBPMS0.43 [87,] RIPK2 RIPK2 0.42 [88,] CBLB CBLB 0.46 [89,] NR1D2 NR1D2 0.47[90,] BTN3A2 BTN3A2 0.38 [91,] SLC7A11 SLC7A11 0.4 [92,] MPZL1 MPZL1 0.3[93,] IGFBP3 IGFBP3 IGFBP3 0.31 [94,] SSA2 SSA2 0.36 [95,] FN1 FN1 FN10.32 [96,] NQO1 NQO1 0.4 [97,] ASPH ASPH 0.36 [98,] ASAH1 ASAH1 0.33[99,] MGLL MGLL 0.35 [100,]  SERPINB6 SERPINB6 0.51 [101,]  HSPA5 HSPA50.33 [102,]  ZFP36L1 ZFP36L1 0.39 [103,]  COL4A2 COL4A2 0.3 [104,] COL4A1 COL4A1 0.3 [105,]  CD44 CD44 0.35 [106,]  SLC39A14 SLC39A14 0.38[107,]  NIPA2 NIPA2 0.36 [108,]  FKBP9 FKBP9 0.48 [109,]  IL6ST IL6ST0.4 [110,]  DKFZP564G2022 DKFZP564G2022 0.39 [111,]  PPAP2B PPAP2B 0.33[112,]  MAP1B MAP1B 0.3 [113,]  MAPK1 MAPK1 0.3 [114,]  MYO1B MYO1B 0.38[115,]  CAST CAST CAST 0.31 [116,]  RRAS2 RRAS2 0.52 [117,]  QKI QKI0.31 [118,]  LHFPL2 LHFPL2 0.36 [119,]  SEPT10 SEPT10 0.38 [120,]  ARHEARHE 0.5 [121,]  KIAA1078 KIAA1078 0.34 [122,]  FTL FTL 0.38 [123,] KIAA0877 KIAA0877 0.41 [124,]  PLCB1 PLCB1 0.3 [125,]  KIAA0802 KIAA08020.32 [126,]  KPNB1 KPNB1 0.37 [127,]  RAB3GAP RAB3GAP 0.43 [128,] SERPINB1 SERPINB1 0.46 [129,]  TIMM17A TIMM17A 0.38 [130,]  SOD2 SOD20.35 [131,]  HLA-A HLA-A HLA-A 0.33 [132,]  NOMO2 NOMO2 0.43 [133,] LOC55831 LOC55831 0.32 [134,]  PHLDA1 PHLDA1 0.32 [135,]  TMEM2 TMEM20.47 [136,]  MLPH MLPH 0.35 [137,]  FAD104 FAD104 0.34 [138,]  LRRC5LRRC5 0.42 [139,]  RAB7L1 RAB7L1 0.41 [140,]  FLJ35036 FLJ35036 0.36[141,]  DOCK10 DOCK10 0.41 [142,]  LRP12 LRP12 0.36 [143,]  TXNDC5TXNDC5 0.4 [144,]  CDC14B CDC14B 0.39 [145,]  HRMT1L1 HRMT1L1 0.38[146,]  CORO1C CORO1C 0.38 [147,]  DNAJC10 DNAJC10 0.31 [148,]  TNPO1TNPO1 0.33 [149,]  LONP LONP 0.32 [150,]  AMIGO2 AMIGO2 0.38 [151,] DNAPTP6 DNAPTP6 0.31 [152,]  ADAMTS1 ADAMTS1 0.37 [153,]  CCL21 [154,] SCARB2 [155,]  MAD2L1BP [156,]  PTS [157,]  NBL1 [158,]  CD151 [159,] CRIP2 [160,]  UGCG [161,]  PRSS11 [162,]  MME [163,]  CBR1 [164,]  DUSP3[165,]  PFN2 [166,]  MICA [167,]  FTH1 [168,]  RHOC [169,]  ZAP128[170,]  PON2 [171,]  COL5A2 [172,]  CST3 [173,]  MCAM [174,]  MMP2[175,]  CTSD [176,]  ALDH3A1 [177,]  CSRP1 [178,]  S100A4 [179,]  CALD1[180,]  CTGF [181,]  CAPG [182,]  TAGLN [183,]  FSTL1 [184,]  SCTR[185,]  BLVRA [186,]  COPEB [187,]  DIPA [188,]  SMARCD3 [189,]  MVP[190,]  PEA15 [191,]  S100A13 [192,]  ECE1

TABLE 22 Vincristine biomarkers. SEQ ID Corre- NO Gene lationMedianprobe  1 SLC25A5 0.32 TCCTGTACTTGTCCTCAGCTTGGGC  2 RPL10 0.38GCCCCACTGGACAACACTGATTCCT  3 RPL12 0.31 TGCCTGCTCCTGTACTTGTCCTCAG  4RPS4X 0.39 AAATGTTTCCTTGTGCCTGCTCCTG  5 EIF5A 0.31TCCTGTACTTGTCCTCAGCTTGGGC  6 BLMH 0.32 AAGCCTATACGTTTCTGTGGAGTAA  7 TBCA0.3 ACTTGTCCTCAGCTTGGGCTTCTTC  8 MDH2 0.34 TCCTGTACTTGTCCTCAGCTTGGGC  9S100A4 0.32 TGGACCCCACTGGCTGAGAATCTGG 10 C14orf139 0.3TTGGACATCTCTAGTGTAGCTGCCA

TABLE 23 Cisplatin biomarkers. SEQ ID Corre- NO Gene lation Medianprobe11 C1QR1 0.3 CACCCAGCTGGTCCTGTGGATGGGA 12 SLA 0.37TGCCTGCTCCTGTACTTGTCCTCAG 13 PTPN7 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 14ZNFN1A1 0.33 CACCCAGCTGGTCCTGTGGATGGGA 15 CENTB1 0.37TTGGACATCTCTAGTGTAGCTGCCA 16 IFI16 0.31 TCCTCCATCACCTGAAACACTGGAC 17ARHGEF6 0.35 TGCCTGCTCCTGTACTTGTCCTCAG 18 SEC31L2 0.32AAGCCTATACGTTTCTGTGGAGTAA 19 CD3Z 0.32 TTGGACATCTCTAGTGTAGCTGCCA 20 GZMB0.3 TCCTCCATCACCTGAAACACTGGAC 21 CD3D 0.34 TCCTCCATCACCTGAAACACTGGAC 22MAP4K1 0.32 CACCCAGCTGGTCCTGTGGATGGGA 23 GPR65 0.39CACCCAGCTGGTCCTGTGGATGGGA 24 PRF1 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 25ARHGAP15 0.35 CACCCAGCTGGTCCTGTGGATGGGA 26 TM6SF1 0.41TGCCTGCTCCTGTACTTGTCCTCAG 27 TCF4 0.4 AAATGTTTCCTTGTGCCTGCTCCTG

TABLE 24 Etoposide biomarkers. SEQ ID Corre- NO Gene lation Medianprobe28 CD99 0.3 AAGCCTATACGTTTCTGTGGAGTAA 29 INSIG1 0.35TCCTTGTGCCTGCTCCTGTACTTGT 30 PRG1 0.34 GCCCCACTGGACAACACTGATTCCT 31 MUF10.35 AAGCCTATACGTTTCTGTGGAGTAA 32 SLA 0.37 CACCCAGCTGGTCCTGTGGATGGGA 33SSBP2 0.37 TGGACCCCACTGGCTGAGAATCTGG 34 GNB5 0.35TCCTTGTGCCTGCTCCTGTACTTGT 35 MFNG 0.33 GCCCCACTGGACAACACTGATTCCT 36PSMB9 0.31 AAGCCTATACGTTTCTGTGGAGTAA 37 EVI2A 0.41TCCTCCATCACCTGAAACACTGGAC 38 PTPN7 0.3 AAGCCTATACGTTTCTGTGGAGTAA 39PTGER4 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 40 CXorf9 0.3GCCCCACTGGACAACACTGATTCCT 41 ZNFN1A1 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC 42CENTB1 0.3 TGGACCCCACTGGCTGAGAATCTGG 43 NAP1L1 0.31TCCTCCATCACCTGAAACACTGGAC 44 HLA-DRA 0.34 TGCCTGCTCCTGTACTTGTCCTCAG 45IFI16 0.38 CACCCAGCTGGTCCTGTGGATGGGA 46 ARHGEF6 0.33TGGACCCCACTGGCTGAGAATCTGG 47 PSCDBP 0.4 AAGCCTATACGTTTCTGTGGAGTAA 48SELPLG 0.35 TTGGACATCTCTAGTGTAGCTGCCA 49 SEC31L2 0.42AAATGTTTCCTTGTGCCTGCTCCTG 50 CD3Z 0.36 TGCCTGCTCCTGTACTTGTCCTCAG 51SH2D1A 0.33 CACCCAGCTGGTCCTGTGGATGGGA 52 GZMB 0.34TGGACCCCACTGGCTGAGAATCTGG 53 SCN3A 0.3 GCCCCACTGGACAACACTGATTCCT 54RAFTLIN 0.39 TCCTCCATCACCTGAAACACTGGAC 55 DOCK2 0.33TGCCTGCTCCTGTACTTGTCCTCAG 56 CD3D 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 57ZAP70 0.35 TCCTCCATCACCTGAAACACTGGAC 58 GPR65 0.35TGGACCCCACTGGCTGAGAATCTGG 59 PRF1 0.32 TGGACCCCACTGGCTGAGAATCTGG 60ARHGAP15 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC 61 NOTCH1 0.31TGCCTGCTCCTGTACTTGTCCTCAG 62 UBASH3A 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 25 Azaguanine biomarkers. SEQ ID Corre- NO Gene lation Medianprobe63 SRM 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 64 SCARB1 0.4TTGGACATCTCTAGTGTAGCTGCCA 65 SIAT1 0.31 AAATGTTTCCTTGTGCCTGCTCCTG 66CUGBP2 0.37 TGGACCCCACTGGCTGAGAATCTGG 67 WASPIP 0.44TCCTGTACTTGTCCTCAGCTTGGGC 68 ITM2A 0.31 AAGCCTATACGTTTCTGTGGAGTAA 69PALM2-AKAP2 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 70 LNK 0.43TTGGACATCTCTAGTGTAGCTGCCA 71 FCGR2A 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 72RUNX3 0.43 TCCTGTACTTGTCCTCAGCTTGGGC 73 EVI2A 0.4AAATGTTTCCTTGTGCCTGCTCCTG 74 BTN3A3 0.4 ACTTGTCCTCAGCTTGGGCTTCTTC 75LCP2 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 76 BCHE 0.35TCCTCCATCACCTGAAACACTGGAC 77 LY96 0.47 TGCCTGCTCCTGTACTTGTCCTCAG 78 LCP10.42 ACTTGTCCTCAGCTTGGGCTTCTTC 79 IFI16 0.33 CACCCAGCTGGTCCTGTGGATGGGA80 MCAM 0.37 TTGGACATCTCTAGTGTAGCTGCCA 81 MEF2C 0.41CACCCAGCTGGTCCTGTGGATGGGA 82 FYN 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 83C1orf38 0.37 AAGCCTATACGTTTCTGTGGAGTAA 84 FCGR2C 0.34TGCCTGCTCCTGTACTTGTCCTCAG 85 TNIK 0.35 AAGCCTATACGTTTCTGTGGAGTAA 86AMPD2 0.3 TCCTGTACTTGTCCTCAGCTTGGGC 87 SEPT6 0.41AAATGTTTCCTTGTGCCTGCTCCTG 88 RAFTLIN 0.39 TCCTTGTGCCTGCTCCTGTACTTGT 89SLC43A3 0.52 CACCCAGCTGGTCCTGTGGATGGGA 90 LPXN 0.54AAGCCTATACGTTTCTGTGGAGTAA 91 CKIP-1 0.33 TCCTGTACTTGTCCTCAGCTTGGGC 92FLJ10539 0.33 TCCTTGTGCCTGCTCCTGTACTTGT 93 FLJ35036 0.36AAGCCTATACGTTTCTGTGGAGTAA 94 DOCK10 0.3 GCCCCACTGGACAACACTGATTCCT 95TRPV2 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 96 IFRG28 0.3TCCTTGTGCCTGCTCCTGTACTTGT 97 LEF1 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 98ADAMTS1 0.36 TGGACCCCACTGGCTGAGAATCTGG

TABLE 26 Carboplatin biomarkers. SEQ ID Corre- NO Gene lationMedianprobe  99 ITGA5 0.43 AAATGTTTCCTTGTGCCTGCTCCTG 100 TNFAIP3 0.4TGCCTGCTCCTGTACTTGTCCTCAG 101 WNT5A 0.34 TCCTCCATCACCTGAAACACTGGAC 102FOXF2 0.36 TGCCTGCTCCTGTACTTGTCCTCAG 103 LOC94105 0.32AAATGTTTCCTTGTGCCTGCTCCTG 104 IFI16 0.38 TCCTCCATCACCTGAAACACTGGAC 105LRRN3 0.33 TTGGACATCTCTAGTGTAGCTGCCA 106 DOCK10 0.4TCCTGTACTTGTCCTCAGCTTGGGC 107 LEPRE1 0.32 GCCCCACTGGACAACACTCATTCCT 108ADAMTS1 0.34 TGGACCCCACTGGCTGAGAATCTGG

TABLE 27 Adriamycin biomarkers. SEQ ID Corre- NO Gene lation Medianprobe109 CD99 0.41 AAGCCTATACGTTTCTGTGGAGTAA 110 ALDOC 0.31TCCTTGTGCCTGCTCCTGTACTTGT 111 SLA 0.35 TGCCTGCTCCTGTACTTGTCCTCAG 112SSBP2 0.34 TCCTCCATCACCTGAAACACTGGAC 113 IL2RG 0.38TCCTTGTGCCTGCTCCTGTACTTGT 114 CXorf9 0.32 TGGACCCCACTGGCTGAGAATCTGG 115RHOH 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 116 ZNFN1A1 0.43TTGGACATCTCTAGTGTAGCTGCCA 117 CENTB1 0.36 AAGCCTATACGTTTCTGTGGAGTAA 118MAP4K1 0.35 TCCTCCATCACCTGAAACACTGGAC 119 CD3G 0.31AAATGTTTCCTTGTGCCTGCTCCTG 120 CCR9 0.34 CACCCAGCTGGTCCTGTGGATGGGA 121CXCR4 0.3 TCCTTGTGCCTGCTCCTGTACTTGT 122 ARHGEF6 0.31TCCTCCATCACCTGAAACACTGGAC 123 SELPLG 0.31 TGGACCCCACTGGCTGAGAATCTGG 124SEC31L2 0.33 TGCCTGCTCCTGTACTTGTCCTCAG 125 CD3Z 0.37ACTTGTCCTCAGCTTGGGCTTCTTC 126 SH2D1A 0.37 TTGGACATCTCTAGTGTAGCTGCCA 127CD1A 0.4 AAGCCTATACGTTTCTGTGGAGTAA 128 LAIR1 0.39AAGCCTATACGTTTCTGTGGAGTAA 129 TRB@ 0.34 TCCTCCATCACCTGAAACACTGGAC 130CD3D 0.33 TCCTTGTGCCTGCTCCTGTACTTGT 131 WBSCR20C 0.34ACTTGTCCTCAGCTTGGGCTTCTTC 132 ZAP70 0.33 TCCTGTACTTGTCCTCAGCTTGGGC 133IFI44 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 134 GPR65 0.31AAGCCTATACGTTTCTGTGGAGTAA 135 AIF1 0.3 CACCCAGCTGGTCCTGTGGATGGGA 136ARHGAP15 0.37 TCCTGTACTTGTCCTCAGCTTGGGC 137 NARF 0.3TCCTCCATCACCTGAAACACTGGAC 138 PACAP 0.32 CACCCAGCTGGTCCTGTGGATGGGA

TABLE 28 Aclarubicin biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 139 RPL12 0.3 AAATGTTTCCTTGTGCCTGCTCCTG 140 RPLP2 0.37TTGGACATCTCTAGTGTAGCTGCCA 141 MYB 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 142ZNFN1A1 0.34 AAATGTTTCCTTGTGCCTGCTCCTG 143 SCAP1 0.33TGCCTGCTCCTGTACTTGTCCTCAG 144 STAT4 0.31 AAATGTTTCCTTGTGCCTGCTCCTG 145SP140 0.4 AAGCCTATACGTTTCTGTGGAGTAA 146 AMPD3 0.3TGCCTGCTCCTGTACTTGTCCTCAG 147 TNFAIP8 0.4 AAGCCTATACGTTTCTGTGGAGTAA 148DDX18 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 149 TAF5 0.3TCCTTGTGCCTGCTCCTGTACTTGT 150 RPS2 0.34 CACCCAGCTGGTCCTGTGGATGGGA 151DOCK2 0.32 AAGCCTATACGTTTCTGTGGAGTAA 152 GPR65 0.35AAGCCTATACGTTTCTGTGGAGTAA 153 HOXA9 0.33 TCCTTGTGCCTGCTCCTGTACTTGT 154FLJ12270 0.31 AAATGTTTCCTTGTGCCTGCTCCTG 155 HNRPD 0.4ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 29 Mitoxantrone biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 156 PGAM1 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 157 DPYSL3 0.36AAATGTTTCCTTGTGCCTGCTCCTG 158 INSIG1 0.32 TCCTTGTGCCTGCTCCTGTACTTGT 159GJA1 0.31 TTGGACATCTCTAGTGTAGCTGCCA 160 BNIP3 0.31TTGGACATCTCTAGTGTAGCTGCCA 161 PRG1 0.39 GCCCCACTGGACAACACTGATTCCT 162G6PD 0.34 TGCCTGCTCCTGTACTTGTCCTCAG 163 PLOD2 0.34GCCCCACTGGACAACACTGATTCCT 164 LOXL2 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 165SSBP2 0.36 TCCTCCATCACCTGAAACACTGGAC 166 C1orf29 0.35TCCTTGTGCCTGCTCCTGTACTTGT 167 TOX 0.35 TCCTTGTGCCTGCTCCTGTACTTGT 168STC1 0.39 TCCTGTACTTGTCCTCAGCTTGGGC 169 TNFRSF1A 0.34AAATGTTTCCTTGTGCCTGCTCCTG 170 NCOR2 0.3 TCCTCCATCACCTGAAACACTGGAC 171NAP1L1 0.32 TCCTTGTGCCTGCTCCTGTACTTGT 172 LOC94105 0.34AAGCCTATACGTTTCTGTGGAGTAA 173 ARHGEF6 0.34 TCCTCCATCACCTGAAACACTGGAC 174GATA3 0.35 TCCTTGTGCCTGCTCCTGTACTTGT 175 TFPI 0.31TCCTGTACTTGTCCTCAGCTTGGGC 176 CD3Z 0.37 AAGCCTATACGTTTCTGTGGAGTAA 177AF1Q 0.33 GCCCCACTGGACAACACTGATTCCT 178 MAP1B 0.34TGCCTGCTCCTGTACTTGTCCTCAG 179 CD3D 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 180BCAT1 0.32 TCCTGTACTTGTCCTCAGCTTGGGC 181 IFI44 0.33TGGACCCCACTGGCTGAGAATCTGG 182 CUTC 0.33 AAATGTTTCCTTGTGCCTGCTCCTG 183NAP1L2 0.33 AAGCCTATACGTTTCTGTGGAGTAA 184 NME7 0.35AAATGTTTCCTTGTGCCTGCTCCTG 185 FLJ21159 0.33 TCCTGTACTTGTCCTCAGCTTGGGC

TABLE 30 Mitomycin biomarkers. SEQ ID Corre- NO Gene lation Medianprobe186 STC1 0.34 TGCCTGCTCCTGTACTTGTCCTCAG 187 GPR65 0.32GCCCCACTGGACAACACTGATTCCT 188 DOCK10 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC 189FAM46A 0.36 TCCTTGTGCCTGCTCCTGTACTTGT 190 LOC54103 0.39ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 31 Paclitaxel (Taxol) biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 191 RPL10 0.31 TCCTCCATCACCTGAAACACTGGAC 192 RPS4X 0.31TCCTCCATCACCTGAAACACTGGAC 193 DKC1 0.3 TCCTTGTGCCTGCTCCTGTACTTGT 194DKFZP564C186 0.32 ACTTGTCCTCAGCTTGGGGTTCTTC 195 PRP19 0.31TGCCTGCTCCTGTACTTGTCCTCAG 196 PAB9P40 0.33 GCCCCACTGGACAACACTGATTCCT 197HSA9761 0.37 AAATGTTTCCTTGTGCCTGCTCCTG 198 GMDS 0.3AAATGTTTCCTTGTGCCTGCTCCTG 199 CEP1 0.3 AAATGTTTCCTTGTGCCTGCTCCTG 200IL13RA2 0.34 AAATGTTTCCTTGTGCCTGCTCCTG 201 MAGEB2 0.41ACTTGTCCTCAGCTTGGGCTTCTTC 202 HMGN2 0.35 CACCCAGCTGGTCCTGTGGATGGGA 203ALMS1 0.3 TCCTCCATCACCTGAAACACTGGAC 204 GPR65 0.31TGCCTGCTCCTGTACTTGTCCTCAG 205 FLJ10774 0.31 TGGACCCCACTGGCTGAGAATCTGG206 NOL8 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 207 DAZAP1 0.32TGCCTGCTCCTGTACTTGTCCTCAG 208 SLC25A15 0.31 TTGGACATCTCTAGTGTAGCTGCCA209 PAF53 0.36 TCCTCCATCACCTGAAACACTGGAC 210 PITPNC1 0.33TCCTCCATCACCTGAAACACTGGAC 211 SPANXC 0.3 TGGACCCCACTGGCTGAGAATCTGG 212KIAA1393 0.33 CACCCAGCTGGTCCTGTGGATGGGA

TABLE 32 Gemcitabine (Gemzar) biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 213 UBE2L6 0.38 CACCCAGCTGGTCCTGTGGATGGGA 214 TAP1 0.33CACCCAGCTGGTCCTGTGGATGGGA 215 F2R 0.3 TCCTGTACTTGTCCTCAGCTTGGGC 216PSMB9 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 217 IL7R 0.31AAGCCTATACGTTTCTGTGGAGTAA 218 TNFAIP8 0.33 AAGCCTATACGTTTCTGTGGAGTAA 219HLA-C 0.33 TGGACCCCACTGGCTGAGAATCTGG 220 IFI44 0.31TGGACCCCACTGGCTGAGAATCTGG

TABLE 33 Taxotere (docetaxel) biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 221 ANP32B 0.45 GCCCCACTGGACAACACTGATTCCT 222 GTF3A 0.31TTGGACATCTCTAGTGTAGCTGCCA 223 TRIM14 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 224SKP2 0.33 GCCCCACTGGACAACACTGATTCCT 225 TRIP13 0.36TCCTGTACTTGTCCTCAGCTTGGGC 226 RFC3 0.45 GCCCCACTGGACAACACTGATTCCT 227CASP7 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 228 TXN 0.36AAGCCTATACGTTTCTGTGGAGTAA 229 MCM5 0.34 AAATGTTTCCTTGTGCCTGCTCCTG 230PTGES2 0.39 AAATGTTTCCTTGTGCCTGCTCCTG 231 OBFC1 0.37TGGACCCCACTGGCTGAGAATCTGG 232 EPB41L4B 0.32 GCCCCACTGGACAACACTGATTCCT233 CALML4 0.31 TCCTCCATCACCTGAAACACTGGAC

TABLE 34 Dexamethasone biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 234 IFITM2 0.38 ATATATGGACCTAGCTTGAGGCAAT 235 UBE2L6 0.32AAGCCTATACGTTTCTGTGGAGTAA 236 ITM2A 0.38 CACCCAGCTGGTCCTGTGGATGGGA 237IL2RG 0.36 TCCTCCATCACCTGAAACACTGGAC 238 GPRASP1 0.36TCCTGTACTTGTCCTCAGCTTGGGC 239 PTPN7 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 240CXorf9 0.36 GCCCCACTGGACAACACTGATTCCT 241 RHOH 0.33TGCCTGCTCCTGTACTTGTCCTCAG 242 GIT2 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 243ZNFN1A1 0.35 TCCTTGTGCCTGCTCCTGTACTTGT 244 CEP1 0.31CACCCAGCTGGTCCTGTGGATGGGA 245 MAP4K1 0.3 AAGCCTATACGTTTCTGTGGAGTAA 246CCR7 0.33 AAATGTTTCCTTGTGCCTGCTCCTG 247 CD3G 0.35CACCCAGCTGGTCCTGTGGATGGGA 248 UCP2 0.3 AAGCCTATACGTTTCTGTGGAGTAA 249GATA3 0.37 TGGACCCCACTGGCTGAGAATCTGG 250 CDKN2A 0.32TCCTGTACTTGTCCTCAGCTTGGGC 251 TARP 0.3 GCCCCACTGGACAACACTGATTCCT 252LAIR1 0.34 TTGGACATCTCTAGTGTAGCTGCCA 253 SH2D1A 0.34TCCTTGTGCCTGCTCCTGTACTTGT 254 SEPT6 0.34 TGCCTGCTCCTGTACTTGTCCTCAG 255HA-1 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 256 CD3D 0.32TCCTCCATCACCTGAAACACTGGAC 257 LST1 0.39 CACCCAGCTGGTCCTGTGGATGGGA 258AIF1 0.35 AAGCCTATACGTTTCTGTGGAGTAA 259 ADA 0.33TGCCTGCTCCTGTACTTGTCCTCAG 260 DATF1 0.41 CACCCAGCTGGTCCTGTGGATGGGA 261ARHGAP15 0.3 TCCTGTACTTGTCCTCAGCTTGGGC 262 PLAC8 0.31CACCCAGCTGGTCCTGTGGATGGGA 263 CECR1 0.31 GCCCCACTGGACAACACTGATTCCT 264LOC81558 0.33 TGGACCCCACTGGCTGAGAATCTGG 265 EHD2 0.37ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 35 Ara-C (Cytarabine hydrochloride) biomarkers. SEQ ID Corre- NOGene lation Medianprobe 266 ITM2A 0.32 TGGACCCCACTGGCTGAGAATCTGG 267RHOH 0.31 AAATGTTTCCTTGTGCCTGCTCCTG 268 PRIM1 0.3TCCTCCATCACCTGAAACACTGGAC 269 CENTB1 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 270NAP1L1 0.31 GCCCCACTGGACAACACTGATTCCT 271 ATP5G2 0.31TCCTCCATCACCTGAAACACTGGAC 272 GATA3 0.33 AAATGTTTCCTTGTGCCTGCTCCTG 273PRKCQ 0.32 AAGCCTATACGTTTCTGTGGAGTAA 274 SH2D1A 0.3GCCCCACTGGACAACACTGATTCCT 275 SEPT6 0.42 ACTTGTCCTCAGCTTGGGCTTCTTC 276NME4 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 277 CD3D 0.31AAGCCTATACGTTTCTGTGGAGTAA 278 CD1E 0.32 TGGACCCCACTGGCTGAGAATCTGG 279ADA 0.34 GCCCCACTGGACAACACTGATTCCT 280 FHOD1 0.31CACCCAGCTGGTCCTGTGGATGGGA

TABLE 36 Methylprednisolone biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 281 CD99 0.31 GCCCCACTGGACAACACTGATTCCT 282 ARHGDIB 0.31TGCCTGCTCCTGTACTTGTCCTCAG 283 ITM2A 0.35 GCCCCACTGGACAACACTGATTCCT 284LGALS9 0.43 TCCTCCATCACCTGAAACACTGGAC 285 INPP5D 0.34TGGACCCCACTGGCTGAGAATCTGG 286 SATB1 0.32 TCCTTGTGCCTGCTCCTGTACTTGT 287TFDP2 0.4 AAATGTTTCCTTGTGCCTGCTCCTG 288 SLA 0.31TGGACCCCACTGGCTGAGAATCTGG 289 IL2RG 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 290MFNG 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 291 SELL 0.33AAATGTTTCCTTGTGCCTGCTCCTG 292 CDW52 0.33 TCCTCCATCACCTGAAACACTGGAC 293LRMP 0.32 TCCTGTACTTGTCCTCAGCTTGGGC 294 ICAM2 0.38CACCCAGCTGGTCCTGTGGATGGGA 295 RIMS3 0.36 TGCCTGCTCCTGTACTTGTCCTCAG 296PTPN7 0.39 TGGACCCCACTGGCTGAGAATCTGG 297 ARHGAP25 0.37TCCTGTACTTGTCCTCAGCTTGGGC 298 LCK 0.3 TCCTCCATCACCTGAAACACTGGAC 299CXorf9 0.3 TTGGACATCTCTAGTGTAGCTGCCA 300 RHOH 0.51AAGCCTATACGTTTCTGTGGAGTAA 301 GIT2 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 302ZNFN1A1 0.53 TCCTTGTGCCTGCTCCTGTACTTGT 303 CENTB1 0.36TCCTCCATCACCTGAAACACTGGAC 304 LCP2 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 305SPI1 0.3 TCCTGTACTTGTCCTCAGCTTGGGC 306 GZMA 0.31AAGCCTATACGTTTCTGTGGAGTAA 307 CEP1 0.37 AAGCCTATACGTTTCTGTGGAGTAA 308CD8A 0.38 TGGACCCCACTGGCTGAGAATCTGG 309 SCAP1 0.32TCCTCCATCACCTGAAACACTGGAC 310 CD2 0.48 GCCCCACTGGACAACACTGATTCCT 311VAV1 0.41 ACTTGTCCTCAGCTTGGGCTTCTTC 312 MAP4K1 0.36TCCTGTACTTGTCCTCAGCTTGGGC 313 CCR7 0.37 ACTTGTCCTCAGCTTGGGCTTCTTC 314C6orf32 0.38 TCCTTGTGCCTGCTCCTGTACTTGT 315 ALOX15B 0.43TGCCTGCTCCTGTACTTGTCCTCAG 316 BRDT 0.33 AAGCCTATACGTTTCTGTGGAGTAA 317CD3G 0.51 AAGCCTATACGTTTCTGTGGAGTAA 318 LTB 0.32ACTTGTCCTCAGCTTGGGCTTCTTC 319 NVL 0.31 TTGGACATCTCTAGTGTAGCTGCCA 320RASGRP2 0.35 TGCCTGCTCCTGTACTTGTCCTCAG 321 LCP1 0.34AAATGTTTCCTTGTGCCTGCTCCTG 322 CXCR4 0.3 AAGCCTATACGTTTCTGTGGAGTAA 323PRKD2 0.33 CACCCAGCTGGTCCTGTGGATGGGA 324 GATA3 0.39TCCTGTACTTGTCCTCAGCTTGGGC 325 KIAA0922 0.36 GCCCCACTGGACAACACTGATTCCT326 TARP 0.49 TCCTCCATCACCTGAAACACTGGAC 327 SEC31L2 0.32ACTTGTCCTCAGCTTGGGCTTCTTC 328 PRKCQ 0.37 TTGGACATCTCTAGTGTAGCTGCCA 329SH2D1A 0.33 AAGCCTATACGTTTCTGTGGAGTAA 330 CHRNA3 0.5AAGCCTATACGTTTCTGTGGAGTAA 331 CD1A 0.44 AAGCCTATACGTTTCTGTGGAGTAA 332LST1 0.36 CACCCAGCTGGTCCTGTGGATGGGA 333 LAIR1 0.47CACCCAGCTGGTCCTGTGGATGGGA 334 CACNA1G 0.33 GCCCCACTGGACAACACTGATTCCT 335TRB@ 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 336 SEPT6 0.33TCCTTGTGCCTGCTCCTGTACTTGT 337 HA-1 0.42 CACCCAGCTGGTCCTGTGGATGGGA 338DOCK2 0.32 TCCTGTACTTGTCCTCAGCTTGGGC 339 CD3D 0.41TCCTGTACTTGTCCTCAGCTTGGGC 340 TRD@ 0.38 TGCCTGCTCCTGTACTTGTCCTCAG 341T3JAM 0.37 TGCCTGCTCCTGTACTTGTCCTCAG 342 FNBP1 0.37TCCTGTACTTGTCCTCAGCTTGGGC 343 CD6 0.4 CACCCAGCTGGTCCTGTGGATGGGA 344 AIF10.31 TGCCTGCTCCTGTACTTGTCCTCAG 345 FOLH1 0.45 TCCTGTACTTGTCCTCAGCTTGGGC346 CD1E 0.58 CACCCAGCTGGTCCTGTGGATGGGA 347 LY9 0.39TCCTTGTGCCTGCTCCTGTACTTGT 348 ADA 0.39 AAATGTTTCCTTGTGCCTGCTCCTG 349CDKL5 0.44 GCCCCACTGGACAACACTGATTCCT 350 TRIM 0.38AAGCCTATACGTTTCTGTGGAGTAA 351 DATF1 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 352RGC32 0.51 TCCTTGTGCCTGCTCCTGTACTTGT 353 ARHGAP15 0.34CACCCAGCTGGTCCTGTGGATGGGA 354 NOTCH1 0.36 TCCTTGTGCCTGCTCCTGTACTTGT 355BIN2 0.31 AAATGTTTCCTTGTGCCTGCTCCTG 356 SEMA4G 0.35AAGCCTATACGTTTCTGTGGAGTAA 357 DPEP2 0.33 CACCCAGCTGGTCCTGTGGATGGGA 358CECR1 0.36 TCCTGTACTTGTCCTCAGCTTGGGC 359 BCL11B 0.33TGCCTGCTCCTGTACTTGTCCTCAG 360 STAG3 0.41 TTGGACATCTCTAGTGTAGCTGCCA 361GALNT6 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 362 UBASH3A 0.3AAATGTTTCCTTGTGCCTGCTCCTG 363 PHEMX 0.38 TCCTCCATCACCTGAAACACTGGAC 364FLJ13373 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 365 LEF1 0.49TCCTCCATCACCTGAAACACTGGAC 366 IL21R 0.42 TTGGACATCTCTAGTGTAGCTGCCA 367MGC17330 0.33 TCCTTGTGCCTGCTCCTGTACTTGT 368 AKAP13 0.53TCCTTGTGCCTGCTCCTGTACTTGT 369 GIMAP5 0.34 AAATGTTTCCTTGTGCCTGCTCCTG

TABLE 37 Methotrexate biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 370 PRPF8 0.34 TCCTCCATCACCTGAAACACTGGAC 371 RPL18 0.34AAGCCTATACGTTTCTGTGGAGTAA 372 GOT2 0.31 CACCCAGCTGGTCCTGTGGATGGGA 373RPL13A 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 374 RPS15 0.39CACCCAGCTGGTCCTGTGGATGGGA 375 RPLP2 0.32 GCCCCACTGGACAACACTGATTCCT 376CSDA 0.39 GCCCCACTGGACAACACTGATTCCT 377 KHDRBS1 0.32TCCTCCATCACCTGAAACACTGGAC 378 SNRPA 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 379IMPDH2 0.39 AAATGTTTCCTTGTGCCTGCTCCTG 380 RPS19 0.47AAATGTTTCCTTGTGCCTGCTCCTG 381 NUP88 0.36 CACCCAGCTGGTCCTGTGGATGGGA 382ATP5D 0.33 TGCCTGCTCCTGTACTTGTCCTCAG 383 PCBP2 0.32AAATGTTTCCTTGTGCCTGCTCCTG 384 ZNF593 0.4 AAATGTTTCCTTGTGCCTGCTCCTG 385HSU79274 0.32 TGGACCCCACTGGCTGAGAATCTGG 386 PRIM1 0.3CACCCAGCTGGTCCTGTGGATGGGA 387 PFDN5 0.33 TCCTCCATCACCTGAAACACTGGAC 388OXA1L 0.37 CACCCAGCTGGTCCTGTGGATGGGA 389 ATIC 0.31ACTTGTCCTCAGCTTGGGCTTCTTC 390 CIAPIN1 0.34 ACTTGTCCTCAGCTTGGGCTTCTTC 391RPS2 0.32 CACCCAGCTGGTCCTGTGGATGGGA 392 PCCB 0.36GCCCCACTGGACAACACTGATTCCT 393 SHMT2 0.34 ACTTGTCCTCAGCTTGGGCTTCTTC 394RPLP0 0.35 AAGCCTATACGTTTCTGTGGAGTAA 395 HNRPA1 0.35TGGACCCCACTGGCTGAGAATCTGG 396 STOML2 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 397SKB1 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 398 GLTSCR2 0.37AAGCCTATACGTTTCTGTGGAGTAA 399 CCNB1IP1 0.3 TCCTTGTGCCTGCTCCTGTACTTGT 400MRPS2 0.33 TTGGACATCTCTAGTGTAGCTGCCA 401 FLJ20859 0.34TGCCTGCTCCTGTACTTGTCCTCAG 402 FLJ12270 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 38 Bleomycin biomarkers. SEQ ID Corre- NO Gene lation Medianprobe403 PFN1 0.45 GCCCCACTGGACAACACTGATTCCT 404 HK1 0.33TTGGACATCTCTAGTGTAGCTGCCA 405 MCL1 0.31 TGGACCCCACTGGCTGAGAATCTGG 406ZYX 0.32 TGGACCCCACTGGCTGAGAATCTGG 407 RAP1B 0.34ACTTGTCCTCAGCTTGGGCTTCTTC 408 GNB2 0.32 CACCCAGCTGGTCCTGTGGATGGGA 409EPAS1 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 410 PGAM1 0.42TGCCTGCTCCTGTACTTGTCCTCAG 411 CKAP4 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 412DUSP1 0.4 AAATGTTTCCTTGTGCCTGCTCCTG 413 MYL9 0.4TTGGACATCTCTAGTGTAGCTGCCA 414 K-ALPHA-1 0.37 TTGGACATCTCTAGTGTAGCTGCCA415 CSDA 0.3 TCCTTGTGCCTGCTCCTGTACTTGT 416 IFITM2 0.36TTGGACATCTCTAGTGTAGCTGCCA 417 ITGA5 0.43 GCCCCACTGGACAACACTGATTCCT 418DPYSL3 0.44 TGGACCCCACTGGCTGAGAATCTGG 419 JUNB 0.32TCCTGTACTTGTCCTCAGCTTGGGC 420 NFKBIA 0.32 TCCTCCATCACCTGAAACACTGGAC 421LAMB1 0.37 AAATGTTTCCTTGTGCCTGCTCCTG 422 FHL1 0.31TGGACCCCACTGGCTGAGAATCTGG 423 INSIG1 0.31 TGGACCCCACTGGCTGAGAATCTGG 424TIMP1 0.48 TGGACCCCACTGGCTGAGAATCTGG 425 GJA1 0.54AAGCCTATACGTTTCTGTGGAGTAA 426 PRG1 0.46 TCCTTGTGCCTGCTCCTGTACTTGT 427EXT1 0.35 TCCTTGTGCCTGCTCCTGTACTTGT 428 DKFZP434J154 0.31GCCCCACTGGACAACACTGATTCCT 429 MVP 0.34 CACCCAGCTGGTCCTGTGGATGGGA 430VASP 0.31 TCCTCCATCACCTGAAACACTGGAC 431 ARL7 0.39TGGACCCCACTGGCTGAGAATCTGG 432 NNMT 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 433TAP1 0.3 TCCTGTACTTGTCCTCAGCTTGGGC 434 PLOD2 0.37GCCCCACTGGACAACACTGATTCCT 435 ATF3 0.42 CACCCAGCTGGTCCTGTGGATGGGA 436PALM2-AKAP2 0.33 TGGACCCCACTGGCTGAGAATCTGG 437 IL8 0.34GCCCCACTGGACAACACTGATTCCT 438 LOXL2 0.32 GCCCCACTGGACAACACTGATTCCT 439IL4R 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 440 DGKA 0.32GCCCCACTGGACAACACTGATTCCT 441 SEC61G 0.41 CACCCAGCTGGTCCTGTGGATGGGA 442RGS3 0.37 TGGACCCCACTGGCTGAGAATCTGG 443 F2R 0.34CACCCAGCTGGTCCTGTGGATGGGA 444 TPM2 0.35 CACCCAGCTGGTCCTGTGGATGGGA 445PSMB9 0.34 CACCCAGCTGGTCCTGTGGATGGGA 446 LOX 0.37TCCTGTACTTGTCCTCAGCTTGGGC 447 STC1 0.35 TCCTCCATCACCTGAAACACTGGAC 448PTGER4 0.31 CACCCAGCTGGTCCTGTGGATGGGA 449 SMAD3 0.38TTGGACATCTCTAGTGTAGCTGCCA 450 WNT5A 0.44 TGGACCCCAGTGGCTGAGAATCTGG 451BDNF 0.34 TCCTCCATCACCTGAAACACTGGAC 452 TNFRSF1A 0.46TCCTCCATCACCTGAAACACTGGAC 453 FLNC 0.34 ACTTGTCCTCAGCTTGGGCTTCTTC 454DKFZP564K0822 0.34 TTGGACATCTCTAGTGTAGCTGCCA 455 FLOT1 0.38TTGGACATCTCTAGTGTAGCTGCCA 456 PTRF 0.39 TGGACCCCACTGGCTGAGAATCTGG 457HLA-B 0.36 TTGGACATCTCTAGTGTAGCTGCCA 458 MGC4083 0.32GCCCCACTGGACAACACTGATTCCT 459 TNFRSF10B 0.34 TGCCTGCTCCTGTACTTGTCCTCAG460 PLAGL1 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 461 PNMA2 0.38GCCCCACTGGACAACACTGATTCCT 462 TFPI 0.38 TCCTGTACTTGTCCTCAGCTTGGGC 463GZMB 0.51 TCCTCCATCACCTGAAACACTGGAC 464 PLAUR 0.35AAGCCTATACGTTTCTGTGGAGTAA 465 FSCN1 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC 466ERP70 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC 467 AF1Q 0.3TTGGACATCTCTAGTGTAGCTGCCA 468 HIC 0.33 TGCCTGCTCCTGTACTTGTCCTCAG 469COL6A1 0.32 AAGCCTATACGTTTCTGTGGAGTAA 470 IFITM3 0.3GCCCCACTGGACAACACTGATTCCT 471 MAP1B 0.38 CACCCAGCTGGTCCTGTGGATGGGA 472FLJ46603 0.37 TCCTCCATCACCTGAAACACTGGAC 473 RAFTLIN 0.34TGGACCCCACTGGCTGAGAATCTGG 474 RRAS 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 475FTL 0.3 CACCCAGCTGGTCCTGTGGATGGGA 476 KIAA0877 0.31CACCCAGCTGGTCCTGTGGATGGGA 477 MT1E 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 478CDC10 0.51 AAATGTTTCCTTGTGCCTGCTCCTG 479 DOCK2 0.32AAGCCTATACGTTTCTGTGGAGTAA 480 RIS1 0.37 ACTTGTCCTCAGCTTGGGCTTCTTC 481BCAT1 0.42 TTGGACATCTCTAGTGTAGCTGCCA 482 PRF1 0.34TCCTCCATCACCTGAAACACTGGAC 483 DBN1 0.36 GCCCCACTGGACAACACTGATTCCT 484MT1K 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 485 TMSB10 0.42GCCCCACTGGACAACACTGATTCCT 486 FLJ10350 0.4 AAATGTTTCCTTGTGCCTGCTCCTG 487C1orf24 0.34 TGCCTGCTCCTGTACTTGTCCTCAG 488 NME7 0.46TCCTGTACTTGTCCTCAGCTTGGGC 489 TMEM22 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 490TPK1 0.37 TCCTCCATCACCTGAAACACTGGAC 491 ELK3 0.38TGCCTGCTCCTGTACTTGTCCTCAG 492 CYLD 0.4 TCCTTGTGCCTGCTCCTGTACTTGT 493ADAMTS1 0.31 AAGCCTATACGTTTCTGTGGAGTAA 494 EHD2 0.41TCCTCCATCACCTGAAACACTGGAC 495 ACTB 0.33 TCCTTGTGCCTGCTCCTGTACTTGT

TABLE 39 Methyl-GAG (methyl glyoxal bis amidinohydrazonedihydrochloride) biomarkers. SEQ ID Corre- NO Gene lation Medianprobe496 SSRP1 0.37 TGCCTGCTCCTGTACTTGTCCTCAG 497 CTSC 0.35CACCCAGCTGGTCCTGTGGATGGGA 498 LBR 0.38 ACTTGTCCTCAGCTTGGGCTTCTTC 499EFNB2 0.31 AAATGTTTCCTTGTGCCTGCTCCTG 500 SERPINA1 0.34TCCTTGTGCCTGCTCCTGTACTTGT 501 SSSCA1 0.32 TCCTGTACTTGTCCTCAGCTTGGGC 502EZH2 0.36 TTGGACATCTCTAGTGTAGCTGCCA 503 MYB 0.33GCCCCACTGGACAACACTGATTCCT 504 PRIM1 0.39 TCCTCCATCACCTGAAACACTGGAC 505H2AFX 0.33 TCCTTGTGCCTGCTCCTGTACTTGT 506 HMGA1 0.35TTGGACATCTCTAGTGTAGCTGCCA 507 HMMR 0.33 TCCTTGTGCCTGCTCCTGTACTTGT 508TK2 0.42 CACCCAGCTGGTCCTGTGGATGGGA 509 WHSC1 0.35AAATGTTTCCTTGTGCCTGCTCCTG 510 DIAPH1 0.34 GCCCCACTGGACAACACTGATTCCT 511LAMB3 0.31 GCCCCACTGGACAACACTGATTCCT 512 DPAGT1 0.42TGCCTGCTCCTGTACTTGTCCTCAG 513 UCK2 0.31 GCCCCACTGGACAACACTGATTCCT 514SERPINB1 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 515 MDN1 0.35TGCCTGCTCCTGTACTTGTCCTCAG 516 G0S2 0.43 CACCCAGCTGGTCCTGTGGATGGGA 517MGC21654 0.36 TGGACCCCACTGGCTGAGAATCTGG 518 GTSE1 0.35ACTTGTCCTCAGCTTGGGCTTCTTC 519 TACC3 0.31 TCCTCCATCACCTGAAACACTGGAC 520PLAC8 0.31 CACCCAGCTGGTCCTGTGGATGGGA 521 HNRPD 0.35TTGGACATCTCTAGTGTAGCTGCCA 522 PNAS-4 0.3 TTGGACATCTCTAGTGTAGCTGCCA

TABLE 40 HDAC inhibitors biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 523. FAU 0.33 TTGGACATCTCTAGTGTAGCTGCCA 524 NOL5A 0.33TGGACCCCACTGGCTGAGAATCTGG 525 ANP32A 0.32 CACCCAGCTGGTCCTGTGGATGGGA 526ARHGDIB 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC 527 LBR 0.31ACTTGTCCTCAGCTTGGGCTTCTTC 528 FABP5 0.33 TCCTCCATCACCTGAAACACTGGAC 529ITM2A 0.32 TTGGACATCTCTAGTGTAGCTGCCA 530 SFRS5 0.34TCCTCCATCACCTGAAACACTGGAC 531 IQGAP2 0.4 CACCCAGCTGGTCCTGTGGATGGGA 532SLC7A6 0.35 AAGCCTATACGTTTCTGTGGAGTAA 533 SLA 0.31TGCCTGCTCCTGTACTTGTCCTCAG 534 IL2RG 0.31 TCCTCCATCACCTGAAACACTGGAC 535MFNG 0.39 TCCTGTACTTGTCCTCAGCTTGGGC 536 GPSM3 0.32TTGGACATCTCTAGTGTAGCTGCCA 537 PIM2 0.3 TTGGACATCTCTAGTGTAGCTGCCA 538EVER1 0.35 GCCCCACTGGACAACACTGATTCCT 539 LRMP 0.35TGCCTGCTCCTGTACTTGTCCTCAG 540 ICAM2 0.44 TCCTGTACTTGTCCTCAGCTTGGGC 541RIMS3 0.43 TGGACCCCACTGGCTGAGAATCTGG 542 FMNL1 0.35TTGGACATCTCTAGTGTAGCTGCCA 543 MYB 0.37 TGCCTGCTCCTGTACTTGTCCTCAG 544PTPN7 0.36 TCCTTGTGCCTGCTCCTGTACTTGT 545 LCK 0.48CACCCAGCTGGTCCTGTGGATGGGA 546 CXorf9 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC 547RHOH 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 548 ZNFN1A1 0.33AAATGTTTCCTTGTGCCTGCTCCTG 549 CENTB1 0.45 CACCCAGCTGGTCCTGTGGATGGGA 550LCP2 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 551 DBT 0.32TCCTGTACTTGTCCTCAGCTTGGGC 552 CEP1 0.31 TTGGACATCTCTAGTGTAGCTGCCA 553IL6R 0.31 TGGACCCCACTGGCTGAGAATCTGG 554 VAV1 0.32TCCTTGTGCCTGCTCCTGTACTTGT 555 MAP4K1 0.3 AAGCCTATACGTTTCTGTGGAGTAA 556CD28 0.36 TCCTTGTGCCTGCTCCTGTACTTGT 557 PTP4A3 0.3TTGGACATCTCTAGTGTAGCTGCCA 558 CD3G 0.33 CACCCAGCTGGTCCTGTGGATGGGA 559LTB 0.4 TCCTGTACTTGTCCTCAGCTTGGGC 560 USP34 0.44GCCCCACTGGACAACACTGATTCCT 561 NVL 0.41 TCCTTGTGCCTGCTCCTGTACTTGT 562CD8B1 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 563 SFRS6 0.31GCCCCACTGGACAACACTGATTCCT 564 LCP1 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 565CXCR4 0.36 TGCCTGCTCCTGTACTTGTCCTCAG 566 PSCDBP 0.33TGGACCCCACTGGCTGAGAATCTGG 567 SELPLG 0.33 TTGGACATCTCTAGTGTAGCTGCCA 568CD3Z 0.3 TCCTTGTGCCTGCTCCTGTACTTGT 569 PRKCQ 0.33TTGGACATCTCTAGTGTAGCTGCCA 570 CD1A 0.34 GCCCCACTGGACAACACTGATTCCT 571GATA2 0.31 TTGGACATCTCTAGTGTAGCTGCCA 572 P2RX5 0.32TGCCTGCTCCTGTACTTGTCCTCAG 573 LAIR1 0.35 TGGACCCCACTGGCTGAGAATCTGG 574C1orf38 0.4 GCCCCACTGGACAACACTGATTCCT 575 SH2D1A 0.44TCCTTGTGCCTGCTCCTGTACTTGT 576 TRB@ 0.33 CACCCAGCTGGTCCTGTGGATGGGA 577SEPT6 0.34 GCCCCACTGGACAACACTGATTCCT 578 HA-1 0.32AAGCCTATACGTTTCTGTGGAGTAA 579 DOCK2 0.3 TCCTTGTGCCTGCTCCTGTACTTGT 580WBSCR20C 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 581 CD3D 0.3ACTTGTCCTCAGCTTGGGCTTCTTC 582 RNASE6 0.31 GCCCCACTGGACAACACTGATTCCT 583SFRS7 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 584 WBSCR20A 0.3AAGCCTATACGTTTCTGTGGAGTAA 585 NUP210 0.31 TTGGACATCTCTAGTGTAGCTGCCA 586CD6 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 587 HNRPA1 0.3GCCCCACTGGACAACACTGATTCCT 588 AIF1 0.34 AAGCCTATACGTTTCTGTGGAGTAA 589CYFIP2 0.38 TGGACCCCACTGGCTGAGAATCTGG 590 GLTSCR2 0.38TCCTTGTGCCTGCTCCTGTACTTGT 591 C11orf2 0.31 AAGCCTATACGTTTCTGTGGAGTAA 592ARHGAP15 0.33 TGGACCCCACTGGCTGAGAATCTGG 593 BIN2 0.35TTGGACATCTCTAGTGTAGCTGCCA 594 SH3TC1 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC 595STAG3 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 596 TM6SF1 0.34ACTTGTCCTCAGCTTGGGCTTCTTC 597 C15orf25 0.33 TCCTCCATCACCTGAAACACTGGAC598 FLJ22457 0.36 AAATGTTTCCTTGTGCCTGCTCCTG 599 PACAP 0.34TGCCTGCTCCTGTACTTGTCCTCAG 600 MGC2744 0.31 GCCCCACTGGACAACACTGATTCCT

TABLE 41 5-Fluorouracil biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 601 RPL18 0.38 AAATGTTTCCTTGTGCCTGCTCCTG 602 RPL10A 0.39TGGACCCCACTGGCTGAGAATCTGG 603 ANAPC5 0.37 ACTTGTCCTCAGCTTGGGCTTCTTC 604EEF1B2 0.3 TCCTGTACTTGTCCTCAGCTTGGGC 605 RPL13A 0.5TGCCTGCTCCTGTACTTGTCCTCAG 606 RPS15 0.4 ACTTGTCCTCAGCTTGGGCTTCTTC 607NDUFAB1 0.38 GCCCCACTGGACAACACTGATTCCT 608 APRT 0.32AAATGTTTCCTTGTGCCTGCTCCTG 609 ZNF593 0.34 TCCTCCATCACCTGAAACACTGGAC 610MRP63 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 611 IL6R 0.41TGGACCCCACTGGCTGAGAATCTGG 612 SART3 0.37 TCCTCCATCACCTGAAACACTGGAC 613UCK2 0.32 GCCCCACTGGACAACACTGATTCCT 614 RPL17 0.31AAGCCTATACGTTTCTGTGGAGTAA 615 RPS2 0.35 CACCCAGCTGGTCCTGTGGATGGGA 616PCCB 0.38 TCCTTGTGCCTGCTCCTGTACTTGT 617 TOMM20 0.32TGGACCCCACTGGCTGAGAATCTGG 618 SHMT2 0.32 TTGGACATCTCTAGTGTAGCTGCCA 619RPLP0 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 620 GTF3A 0.32CACCCAGCTGGTCCTGTGGATGGGA 621 STOML2 0.33 TGGACCCCACTGGCTGAGAATCTGG 622DKFZp564J157 0.4 AAATGTTTCCTTGTGCCTGCTCCTG 623 MRPS2 0.32TCCTGTACTTGTCCTCAGCTTGGGC 624 ALG5 0.3 TTGGACATCTCTAGTGTAGCTGCCA 625CALML4 0.33 CACCCAGCTGGTCCTGTGGATGGGA

TABLE 42 Radiation sensitivity biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 626 TRA1 0.36 TGGACCCCACTGGCTGAGAATCTGG 627 ACTN4 0.36ACTTGTCCTCAGCTTGGGCTTCTTC 628 CALM1 0.32 TCCTCCATCACCTGAAACACTGGAC 629CD63 0.32 TCCTGTACTTGTCCTCAGCTTGGGC 630 FKBP1A 0.38TGGACCCCACTGGCTGAGAATCTGG 631 CALU 0.47 ACTTGTCCTCAGCTTGGGCTTCTTC 632IQGAP1 0.37 TTGGACATCTCTAGTGTAGCTGCCA 633 MGC8721 0.35AAATGTTTCCTTGTGCCTGCTCCTG 634 STAT1 0.37 TGGACCCCACTGGCTGAGAATCTGG 635TACC1 0.41 ACTTGTCCTCAGCTTGGGCTTCTTC 636 TM4SF8 0.33AAGCCTATACGTTTCTGTGGAGTAA 637 CD59 0.31 TCCTCCATCACCTGAAACACTGGAC 638CKAP4 0.45 TCCTTGTGCCTGCTCCTGTACTTGT 639 DUSP1 0.38TCCTGTACTTGTCCTCAGCTTGGGC 640 RCN1 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 641MGC8902 0.35 TGCCTGCTCCTGTACTTGTCCTCAG 642 RRBP1 0.31ACTTGTCCTCAGCTTGGGCTTCTTC 643 PRNP 0.42 TTGGACATCTCTAGTGTAGCTGCCA 644IER3 0.34 GCCCCACTGGACAACACTGATTCCT 645 MARCKS 0.43GCCCCACTGGACAACACTGATTCCT 646 FER1L3 0.47 TGCCTGCTCCTGTACTTGTCCTCAG 647SLC20A1 0.41 ACTTGTCCTCAGCTTGGGCTTCTTC 648 HEXB 0.46AAATGTTTCCTTGTGCCTGCTCCTG 649 EXT1 0.47 CACCCAGCTGGTCCTGTGGATGGGA 650TJP1 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 651 CTSL 0.38TCCTGTACTTGTCCTCAGCTTGGGC 652 SLC39A6 0.36 TCCTGTACTTGTCCTCAGCTTGGGC 653RIOK3 0.38 TCCTCCATCACCTGAAACACTGGAC 654 CRK 0.37TGCCTGCTCCTGTACTTGTCCTCAG 655 NNMT 0.37 TGCCTGCTCCTGTACTTGTCCTCAG 656TRAM2 0.35 TTGGACATCTCTAGTGTAGCTGCCA 657 ADAM9 0.52TCCTGTACTTGTCCTCAGCTTGGGC 658 PLSCR1 0.35 TGGACCCCACTGGCTGAGAATCTGG 659PRSS23 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 660 PLOD2 0.36TGCCTGCTCCTGTACTTGTCCTCAG 661 NPC1 0.39 TGCCTGCTCCTGTACTTGTCCTCAG 662TOB1 0.37 CACCCAGCTGGTCCTGTGGATGGGA 663 GFPT1 0.47CACCCAGCTGGTCCTGTGGATGGGA 664 IL8 0.36 AAATGTTTCCTTGTGCCTGCTCCTG 665PYGL 0.46 TCCTCCATCACCTGAAACACTGGAC 666 LOXL2 0.49TTGGACATCTCTAGTGTAGCTGCCA 667 KIAA0355 0.36 TCCTTGTGCCTGCTCCTGTACTTGT668 UGDH 0.49 TTGGACATCTCTAGTGTAGCTGCCA 669 PURA 0.32TGCCTGCTCCTGTACTTGTCCTCAG 670 ULK2 0.37 AAGCCTATACGTTTCTGTGGAGTAA 671CENTG2 0.35 GCCCCACTGGACAACACTGATTCCT 672 CAP350 0.31GCCCCACTGGACAACACTGATTCCT 673 CXCL1 0.36 TCCTGTACTTGTCCTCAGCTTGGGC 674BTN3A3 0.35 AAGCCTATACGTTTCTGTGGAGTAA 675 WNT5A 0.3AAGCCTATACGTTTCTGTGGAGTAA 676 FOXF2 0.44 AAATGTTTCCTTGTGCCTGCTCCTG 677LPHN2 0.34 GCCCCACTGGACAACACTGATTCCT 678 CDH11 0.39TGGACCCCACTGGCTGAGAATCTGG 679 P4HA1 0.33 TCCTCCATCACCTGAAACACTGGAC 680GRP58 0.44 CACCCAGCTGGTCCTGTGGATGGGA 681 DSIPI 0.44TGGACCCCACTGGCTGAGAATCTGG 682 MAP1LC3B 0.5 AAGCCTATACGTTTCTGTGGAGTAA 683GALIG 0.36 AAATGTTTCCTTGTGCCTGCTCCTG 684 IGSF4 0.4TCCTCCATCACCTGAAACACTGGAC 685 IRS2 0.35 TGGACCCCACTGGCTGAGAATCTGG 686ATP2A2 0.35 CACCCAGCTGGTCCTGTGGATGGGA 687 OGT 0.3TCCTGTACTTGTCCTCAGCTTGGGC 688 TNFRSF10B 0.31 AAGCCTATACGTTTCTGTGGAGTAA689 KIAA1128 0.35 CACCCAGCTGGTCCTGTGGATGGGA 690 TM4SF1 0.35CACCCAGCTGGTCCTGTGGATGGGA 691 RIPK2 0.42 TGCCTGCTCCTGTACTTGTCCTCAG 692NR1D2 0.47 TTGGACATCTCTAGTGTAGCTGCCA 693 SSA2 0.36TTGGACATCTCTAGTGTAGCTGCCA 694 NQO1 0.4 AAGCCTATACGTTTCTGTGGAGTAA 695ASPH 0.36 TGCCTGCTCCTGTACTTGTCCTCAG 696 ASAH1 0.33ACTTGTCCTCAGCTTGGGCTTCTTC 697 MGLL 0.35 TGGACCCCACTGGCTGAGAATCTGG 698SERPINB6 0.51 AAGCCTATACGTTTCTGTGGAGTAA 699 HSPA5 0.33TCCTTGTGCCTGCTCCTGTACTTGT 700 ZFP36L1 0.39 TCCTTGTGCCTGCTCCTGTACTTGT 701COL4A1 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC 702 NIPA2 0.36ACTTGTCCTCAGCTTGGGCTTCTTC 703 FKBP9 0.48 AAATGTTTCCTTGTGCCTGCTCCTG 704IL6ST 0.4 GCCCCACTGGACAACACTGATTCCT 705 DKFZP564G2022 0.39TTGGACATCTCTAGTGTAGCTGCCA 706 PPAP2B 0.33 TGGACCCCACTGGCTGAGAATCTGG 707MAP1B 0.3 CACCCAGCTGGTCCTGTGGATGGGA 708 MAPK1 0.3TGGACCCCACTGGCTGAGAATCTGG 709 MYO1B 0.38 ACTTGTCCTCAGCTTGGGCTTCTTC 710CAST 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 711 RRAS2 0.52AAATGTTTCCTTGTGCCTGCTCCTG 712 QKI 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 713LHFPL2 0.36 TCCTTGTGCCTGCTCCTGTACTTGT 714 SEPT10 0.38GCCCCACTGGACAACACTGATTCCT 715 ARHE 0.5 AAGCCTATACGTTTCTGTGGAGTAA 716KIAA1078 0.34 AAGCCTATACGTTTCTGTGGAGTAA 717 FTL 0.38TCCTGTACTTGTCCTCAGCTTGGGC 718 KIAA0877 0.41 AAATGTTTCCTTGTGCCTGCTCCTG719 PLCB1 0.3 AAGCCTATACGTTTCTGTGGAGTAA 720 KIAA0802 0.32TGCCTGCTCCTGTACTTGTCCTCAG 721 RAB3GAP 0.43 TGCCTGCTCCTGTACTTGTCCTCAG 722SERPINB1 0.46 TGCCTGCTCCTGTACTTGTCCTCAG 723 TIMM17A 0.38AAATGTTTCCTTGTGCCTGCTCCTG 724 SOD2 0.35 TTGGACATCTCTAGTGTAGCTGCCA 725HLA-A 0.33 TTGGACATCTCTAGTGTAGCTGCCA 726 NOMO2 0.43CACCCAGCTGGTCCTGTGGATGGGA 727 LOC55831 0.32 TCCTGTACTTGTCCTCAGCTTGGGC728 PHLDA1 0.32 CACCCAGCTGGTCCTGTGGATGGGA 729 TMEM2 0.47TGGACCCCACTGGCTGAGAATCTGG 730 MLPH 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC 731FAD104 0.34 ACTTGTCCTCAGCTTGGGCTTCTTC 732 LRRC5 0.42CACCCAGCTGGTCCTGTGGATGGGA 733 RAB7L1 0.41 TTGGACATCTCTAGTGTAGCTGCCA 734FLJ35036 0.36 TCCTGTACTTGTCCTCAGCTTGGGC 735 DOCK10 0.41TCCTCCATCACCTGAAACACTGGAC 736 LRP12 0.36 AAGCCTATACGTTTCTGTGGAGTAA 737TXNDC5 0.4 ACTTGTCCTCAGCTTGGGCTTCTTC 738 CDC14B 0.39TGCCTGCTCCTGTACTTGTCCTCAG 739 HRMT1L1 0.38 CACCCAGCTGGTCCTCTGGATGGGA 740DNAJC10 0.31 TTGGACATCTCTAGTGTAGCTGCCA 741 TNPO1 0.33GCCCCACTGGACAACACTGATTCCT 742 LONP 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 743AMIGO2 0.38 AAGCCTATACGTTTCTGTGGAGTAA 744 DNAPTP6 0.31TGCCTGCTCCTGTACTTGTCCTCAG 745 ADAMTS1 0.37 TTGGACATCTCTAGTGTAGCTGCCA

TABLE 43 Rituximab (e.g., Mabthera) biomarkers. SEQ ID Corre- NO Genelation Medianprobe 746 PSMB2 0.89 TCCTCCATCACCTGAAACACTGGAC 747 BAT10.88 AAGCCTATACGTTTCTGTGGAGTAA 748 ASCC3L1 0.89TCCTTGTGCCTGCTCCTGTACTTGT 749 SET 0.94 AAATGTTTCCTTGTGCCTGCTCCTG 750YWHAZ 0.83 TCCTTGTGCCTGCTCCTGTACTTGT 751 GLUL 0.8TGGACCCCACTGGCTGAGAATCTGG 752 LDHA 0.8 TCCTTGTGCCTGCTCCTGTACTTGT 753HMGB1 0.84 AAATGTTTCCTTGTGCCTGCTCCTG 754 SFRS2 0.87AAATGTTTCCTTGTGCCTGCTCCTG 755 DPYSL2 0.82 TCCTGTACTTGTCCTCAGCTTGGGC 756MGC8721 0.82 CACCCAGCTGGTCCTGTGGATGGGA 757 NOL5A 0.86TGCCTGCTCCTGTACTTGTCCTCAG 758 SFRS10 0.88 AAATGTTTCCTTGTGCCTGCTCCTG 759SF3B1 0.82 TCCTGTACTTGTCCTCAGCTTGGGC 760 K-ALPHA-1 0.86TGCCTGCTCCTGTACTTGTCCTCAG 761 TXNRD1 0.86 TGGACCCCACTGGCTGAGAATCTGG 762ARHGDIB 0.83 CACCCAGCTGGTCCTGTGGATGGGA 763 ZFP36L2 0.92TTGGACATCTCTAGTGTAGCTGCCA 764 DHX15 0.81 TGGACCCCACTGGCTGAGAATCTGG 765SOX4 0.85 CACCCAGCTGGTCCTGTGGATGGGA 766 GRSF1 0.81TGGACCCCACTGGCTGAGAATCTGG 767 MCM3 0.85 GCCCCACTGGACAACACTGATTCCT 768IFITM1 0.82 TCCTCCATCACCTGAAACACTGGAC 769 RPA2 0.86TCCTCCATCACCTGAAACACTGGAC 770 LBR 0.87 ACTTGTCCTCAGCTTGGGCTTCTTC 771CKS1B 0.85 AAGCCTATACGTTTCTGTGGAGTAA 772 NASP 0.82TGGACCCCACTGGCTGAGAATCTGG 773 HNRPDL 0.81 TCCTCCATCACCTGAAACACTGGAC 774CUGBP2 0.81 TGCCTGCTCCTGTACTTGTCCTCAG 775 PTBP1 0.87TCCTTGTGCCTGCTCCTGTACTTGT 776 ARL7 0.83 TTGGACATCTCTAGTGTAGCTGCCA 777CTCF 0.83 ACTTGTCCTCAGCTTGGGCTTCTTC 778 HMGCR 0.86TCCTTGTGCCTGCTCCTGTACTTGT 779 ITM2A 0.88 AAATGTTTCCTTGTGCCTGCTCCTG 780SFRS3 0.93 TCCTTGTGCCTGCTCCTGTACTTGT 781 SRPK2 0.82TCCTTGTGCCTGCTCCTGTACTTGT 782 JARID2 0.92 CACCCAGCTGGTCCTGTGGATGGGA 783M96 0.84 TCCTGTACTTGTCCTCAGCTTGGGC 784 MAD2L1 0.87TCCTCCATCACCTGAAACACTGGAC 785 SATB1 0.81 ACTTGTCCTCAGCTTGGGCTTCTTC 786TMPO 0.9 ACTTGTCCTCAGCTTGGGCTTCTTC 787 SIVA 0.84ACTTGTCCTCAGCTTGGGCTTCTTC 788 SEMA4D 0.9 TCCTCCATCACCTGAAACACTGGAC 789TFDP2 0.87 TCCTTGTGCCTGCTCCTGTACTTGT 790 SKP2 0.86AAGCCTATACGTTTCTGTGGAGTAA 791 SH3YL1 0.88 GCCCCACTGGACAACACTGATTCCT 792RFC4 0.87 TCCTCCATCACCTGAAACACTGGAC 793 PCBP2 0.83AAGCCTATACGTTTCTGTGGAGTAA 794 IL2RG 0.84 GCCCCACTGGACAACACTGATTCCT 795CDC45L 0.89 TCCTGTACTTGTCCTCAGCTTGGGC 796 GTSE1 0.83TTGGACATCTCTAGTGTAGCTGCCA 797 KIF11 0.85 AAGCCTATACGTTTCTGTGGAGTAA 798FEN1 0.88 TTGGACATCTCTAGTGTAGCTGCCA 799 MYB 0.9TGGACCCCACTGGCTGAGAATCTGG 800 LCK 0.87 TCCTCCATCACCTGAAACACTGGAC 801CENPA 0.84 GCCCCACTGGACAACACTGATTCCT 802 CCNE2 0.84GCCCCACTGGACAACACTGATTCCT 803 H2AFX 0.88 TTGGACATCTCTAGTGTAGCTGCCA 804SNRPG 0.84 TCCTCCATCACCTGAAACACTGGAC 805 CD3G 0.94TCCTTGTGCCTGCTCCTGTACTTGT 806 STK6 0.9 ACTTGTCCTCAGCTTGGGGTTCTTC 807PTP4A2 0.81 TGCCTGCTCCTGTACTTGTCCTCAG 808 FDFT1 0.91AAATGTTTCCTTGTGCCTGCTCCTG 809 HSPA8 0.84 AAATGTTTCCTTGTGCCTGCTCCTG 810HNRPR 0.94 TCCTTGTGCCTGCTCCTGTACTTGT 811 MCM7 0.92AAATGTTTCCTTGTGCCTGCTCCTG 812 SFRS6 0.85 TGGACCCCACTGGCTGAGAATCTGG 813PAK2 0.8 CACCCAGCTGGTCCTGTGGATGGGA 814 LCP1 0.85TCCTGTACTTGTCCTCAGCTTGGGC 815 STAT3 0.81 ACTTGTCCTCAGCTTGGGCTTCTTC 816OK/SW-cl.56 0.8 TCCTTGTGCCTGCTCCTGTACTTGT 817 WHSC1 0.81TGGACCCCACTGGCTGAGAATCTGG 818 DIAPH1 0.88 AAGCCTATACGTTTCTGTGGAGTAA 819KIF2C 0.88 TCCTGTACTTGTCCTCAGCTTGGGC 820 HDGFRP3 0.89CACCCAGCTGGTCCTGTGGATGGGA 821 PNMA2 0.93 TTGGACATCTCTAGTGTAGCTGCCA 822GATA3 0.93 TCCTGTACTTGTCCTCAGCTTGGGC 823 BUB1 0.88AAATGTTTCCTTGTGCCTGCTCCTG 824 TPX2 0.8 CACCCAGCTGGTCCTGTGGATGGGA 825SH2D1A 0.86 TCCTTGTGCCTGCTCCTGTACTTGT 826 TNFAIP8 0.9TCCTCCATCACCTGAAACACTGGAC 827 CSE1L 0.83 AAATGTTTCCTTGTGCCTGCTCCTG 828MCAM 0.8 TCCTGTACTTGTCCTCAGCTTGGGC 829 AF1Q 0.83GCCCCACTGGACAACACTGATTCCT 830 CD47 0.86 CACCCAGCTGGTCCTGTGGATGGGA 831SFRS1 0.85 AAGCCTATACGTTTCTGTGGAGTAA 832 FYB 0.92TCCTGTACTTGTCCTCAGCTTGGGC 833 TRB@ 0.84 ACTTGTCCTCAGCTTGGGCTTCTTC 834CXCR4 0.94 GCCCCACTGGACAACACTGATTCCT 835 H3F3B 0.84TCCTCCATCACCTGAAACACTGGAC 836 MKI67 0.83 ACTTGTCCTCAGCTTGGGCTTCTTC 837MAC30 0.82 TCCTTGTGCCTGCTCCTGTACTTGT 838 ARID5B 0.88AAGCCTATACGTTTCTGTGGAGTAA 839 LOC339287 0.81 AAGCCTATACGTTTCTGTGGAGTAA840 CD3D 0.82 TCCTTGTGCCTGCTCCTGTACTTGT 841 ZAP70 0.87AAGCCTATACGTTTCTGTGGAGTAA 842 LAPTM4B 0.83 TCCTCCATCACCTGAAACACTGGAC 843SFRS7 0.87 TCCTTGTGCCTGCTCCTGTACTTGT 844 HNRPA1 0.9AAGCCTATACGTTTCTGTGGAGTAA 845 HSPCA 0.88 AAGCCTATACGTTTCTGTGGAGTAA 846AIF1 0.82 TCCTTGTGCCTGCTCCTGTACTTGT 847 GTF3A 0.87AAGCCTATACGTTTCTGTGGAGTAA 848 MCM5 0.91 TTGGACATCTCTAGTGTAGCTGCCA 849GTL3 0.85 AAGCCTATACGTTTCTGTGGAGTAA 850 ZNF22 0.89TGCCTGCTCCTGTACTTGTCCTCAG 851 FLJ22794 0.83 GCCCCACTGGACAACACTGATTCCT852 LZTFL1 0.89 ACTTGTCCTCAGCTTGGGCTTCTTC 853 e(y)2 0.87TCCTCCATCACCTGAAACACTGGAC 854 FLJ20152 0.92 TCCTCCATCACCTGAAACACTGGAC855 C10orf3 0.86 ACTTGTCCTCAGCTTGGGCTTCTTC 856 NRN1 0.86AAATGTTTCCTTGTGCCTGCTCCTG 857 FLJ10858 0.81 GCCCCACTGGACAACACTGATTCCT858 BCL11B 0.89 GCCCCACTGGACAACACTGATTCCT 859 ASPM 0.91AAGCCTATACGTTTCTGTGGAGTAA 860 LEF1 0.9 TTGGACATCTCTAGTGTAGCTGCCA 861LOC146909 0.83 ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 44 5-Aza-2′-deoxycytidine (decitabine) biomarkers. SEQ ID Corre-NO Gene lation Medianprobe 862 CD99 0.31 TTGGACATCTCTAGTGTAGCTGCCA 863SNRPA 0.32 TCCTGTACTTGTCCTCAGCTTGGGC 864 CUGBP2 0.32TCCTGTACTTGTCCTCAGCTTGGGC 865 STAT5A 0.32 GCCCCACTGGACAACACTGATTCCT 866SLA 0.38 TTGGACATCTCTAGTGTAGCTGCCA 867 IL2RG 0.33TGGACCCCACTGGCTGAGAATCTGG 868 GTSE1 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC 869MYB 0.36 TGGACCCCACTGGCTGAGAATCTGG 870 PTPN7 0.33TCCTGTACTTGTCCTCAGCTTGGGC 871 CXorf9 0.42 TCCTGTACTTGTCCTCAGCTTGGGC 872RHOH 0.38 AAATGTTTCCTTGTGCCTGCTCCTG 873 ZNFN1A1 0.33AAGCCTATACGTTTCTGTGGAGTAA 874 CENTB1 0.35 CACCCAGCTGGTCCTGTGGATGGGA 875LCP2 0.3 AAATGTTTCCTTGTGCCTGCTCCTG 876 HIST1H4C 0.33TGGACCCCACTGGCTGAGAATCTGG 877 CCR7 0.37 TGCCTGCTCCTGTACTTGTCCTCAG 878APOBEC3B 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 879 MCM7 0.31TGGACCCCACTGGCTGAGAATCTGG 880 LCP1 0.31 AAGCCTATACGTTTCTGTGGAGTAA 881SELPLG 0.4 TGGACCCCACTGGCTGAGAATCTGG 882 CD3Z 0.35TCCTGTACTTGTCCTCAGCTTGGGC 883 PRKCQ 0.39 TGCCTGCTCCTGTACTTGTCCTCAG 884GZMB 0.32 GCCCCACTGGACAACACTGATTCCT 885 SCN3A 0.4AAGCCTATACGTTTCTGTGGAGTAA 886 LAIR1 0.35 TGCCTGCTCCTGTACTTGTCCTCAG 887SH2D1A 0.35 GCCCCACTGGACAACACTGATTCCT 888 SEPT6 0.35ACTTGTCCTCAGCTTGGGCTTCTTC 889 CG018 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC 890CD3D 0.31 TGGACCCCACTGGCTGAGAATCTGG 891 C18orf10 0.33TCCTTGTGCCTGCTCCTGTACTTGT 892 PRF1 0.31 TCCTCCATCACCTGAAACACTGGAC 893AIF1 0.31 TTGGACATCTCTAGTGTAGCTGCCA 894 MCM5 0.31ACTTGTCCTCAGCTTGGGCTTCTTC 895 LPXN 0.35 TCCTCCATCACCTGAAACACTGGAC 896C22orf18 0.33 AAATGTTTCCTTGTGCCTGCTCCTG 897 ARHGAP15 0.31AAATGTTTCCTTGTGCCTGCTCCTG 898 LEF1 0.43 GCCCCACTGGACAACACTGATTCCT

TABLE 45 Idarubicin biomarkers. SEQ ID Corre- NO Gene lation Medianprobe899 SLC9A3R1 0.31 TGGACCCCACTGGCTGAGAATCTGG 900 RPS19 0.32TGGACCCCACTGGCTGAGAATCTGG 901 ITM2A 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 902SSBP2 0.31 AAGCCTATACGTTTCTGTGGAGTAA 903 CXorf9 0.31TCCTGTACTTGTCCTCAGCTTGGGC 904 RHOH 0.32 TCCTCCATCACCTGAAACACTGGAC 905ZNFN1A1 0.36 AAATGTTTCCTTGTGCCTGCTCCTG 906 FXYD2 0.35CACCCAGCTGGTCCTGTGGATGGGA 907 CCR9 0.39 TGGACCCCACTGGCTGAGAATCTGG 908NAP1L1 0.3 TTGGACATCTCTAGTGTAGCTGCCA 909 CXCR4 0.31AAATGTTTCCTTGTGCCTGCTCCTG 910 SH2D1A 0.3 TCCTGTACTTGTCCTCAGCTTGGGC 911CD1A 0.3 AAGCCTATACGTTTCTGTGGAGTAA 912 TRB@ 0.32AAATGTTTCCTTGTGCCTGCTCCTG 913 SEPT6 0.32 GCCCCACTGGACAACACTGATTCCT 914RPS2 0.33 TGCCTGCTCCTGTACTTGTCCTCAG 915 DOCK2 0.32TGCCTGCTCCTGTACTTGTCCTCAG 916 CD3D 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 917CD6 0.3 GCCCCACTGGACAACACTGATTCCT 918 ZAP70 0.34ACTTGTCCTCAGCTTGGGCTTCTTC 919 AIF1 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 920CD1E 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 921 CYFIP2 0.3TTGGACATCTCTAGTGTAGCTGCCA 922 ADA 0.41 TCCTGTACTTGTCCTCAGCTTGGGC 923TRIM 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 924 GLTSCR2 0.32TGCCTGCTCCTGTACTTGTCCTCAG 925 FLJ10858 0.35 GCCCCACTGGACAACACTGATTCCT926 BCL11B 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 927 GIMAP6 0.36TGCCTGCTCCTGTACTTGTCCTCAG 928 STAG3 0.34 TTGGACATCTCTAGTGTAGCTGCCA 929UBASH3A 0.39 ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 46 Melphalan biomarkers. SEQ ID Corre- NO Gene lation Medianprobe 930 CD99 0.31 TGGACCCCACTGGCTGAGAATCTGG  931 HLA-DPB1 0.32TGCCTGCTCCTGTACTTGTCCTCAG  932 ARHGDIB 0.35 TGCCTGCTCCTGTACTTGTCCTCAG 933 IFITM1 0.33 CACCCAGCTGGTCCTGTGGATGGGA  934 UBE2L6 0.32TCCTTGTGCCTGCTCCTGTACTTGT  935 ITM2A 0.37 TCCTTGTGCCTGCTCCTGTACTTGT  936SERPINA1 0.31 AAATGTTTCCTTGTGCCTGCTCCTG  937 STAT5A 0.38AAATGTTTCCTTGTGCCTGCTCCTG  938 INPP5D 0.37 TCCTTGTGCCTGCTCCTGTACTTGT 939 DGKA 0.3 TGCCTGCTCCTGTACTTGTCCTCAG  940 SATB1 0.34TGCCTGCTCCTGTACTTGTCCTCAG  941 SEMA4D 0.37 AAATGTTTCCTTGTGCCTGCTCCTG 942 TFDP2 0.31 CACCCAGCTGGTCCTGTGGATGGGA  943 SLA 0.49TCCTCCATCACCTGAAACACTGGAC  944 IL2RG 0.42 CACCCAGCTGGTCCTGTGGATGGGA  945CD48 0.33 TCCTTGTGCCTGCTCCTGTACTTGT  946 MFNG 0.48ACTTGTCCTCAGCTTGGGCTTCTTC  947 ALOX5AP 0.3 CACCCAGCTGGTCCTGTGGATGGGA 948 GPSM3 0.31 AAGCCTATACGTTTCTGTGGAGTAA  949 PSMB9 0.34GCCCCACTGGACAACACTGATTCCT  950 KIAA0711 0.37 TGGACCCCACTGGCTGAGAATCTGG 951 SELL 0.32 AAATGTTTCCTTGTGCCTGCTCCTG  952 ADA 0.31TGCCTGCTCCTGTACTTGTCCTCAG  953 EDG1 0.49 TTGGACATCTCTAGTGTAGCTGCCA  954RIMS3 0.3 CACCCAGCTGGTCCTGTGGATGGGA  955 FMNL1 0.33AAGCCTATACGTTTCTGTGGAGTAA  956 MYB 0.3 GCCCCACTGGACAACACTGATTCCT  957PTPN7 0.34 AAATGTTTCCTTGTGCCTGCTCCTG  958 LCK 0.31AAATGTTTCCTTGTGCCTGCTCCTG  959 CXorf9 0.55 CACCCAGCTGGTCCTGTGGATGGGA 960 RHOH 0.35 TGGACCCCACTGGCTGAGAATCTGG  961 ZNFN1A1 0.31ACTTGTCCTCAGCTTGGGCTTCTTC  962 CENTB1 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 963 LCP2 0.32 TCCTTGTGCCTGCTCCTGTACTTGT  964 FXYD2 0.55CACCCAGCTGGTCCTGTGGATGGGA  965 CD1D 0.44 AAGCCTATACGTTTCTGTGGAGTAA  966BATF 0.32 TGCCTGCTCCTGTACTTGTCCTCAG  967 STAT4 0.33TCCTCCATCACCTGAAACACTGGAC  968 VAV1 0.31 TCCTCCATCACCTGAAACACTGGAC  969MAP4K1 0.39 CACCCAGCTGGTCCTGTGGATGGGA  970 CCR7 0.44TCCTGTACTTGTCCTCAGCTTGGGC  971 PDE4C 0.32 TCCTGTACTTGTCCTCAGCTTGGGC  972CD3G 0.32 AAGCCTATACGTTTCTGTGGAGTAA  973 CCR9 0.36TTGGACATCTCTAGTGTAGGTGCCA  974 SP110 0.34 TCCTGTACTTGTCCTCAGCTTGGGC  975LCP1 0.35 AAATGTTTCCTTGTGCCTGCTCCTG  976 IFI16 0.32GCCCCACTGGACAACACTGATTCCT  977 CXCR4 0.36 ACTTGTCCTCAGCTTGGGCTTCTTC  978ARHGEF6 0.47 AAGCCTATACGTTTCTGTGGAGTAA  979 GATA3 0.55TTGGACATCTCTAGTGTAGCTGCCA  980 SELPLG 0.47 TTGGACATCTCTAGTGTAGCTGCCA 981 SEG31L2 0.36 TGGACCCCACTGGCTGAGAATCTGG  982 CD3Z 0.5TTGGACATCTCTAGTGTAGCTGCCA  983 PRKCQ 0.56 GCCGCACTGGACAACACTGATTCCT  984SH2D1A 0.33 TCCTCCATCACCTGAAACACTGGAC  985 GZMB 0.39TGCCTGCTCCTGTACTTGTCCTCAG  986 CD1A 0.55 TGCCTGCTCCTGTACTTGTCCTCAG  987SCN3A 0.64 CACCCAGCTGGTCCTGTGGATGGGA  988 LAIR1 0.32CACCCAGCTGGTCCTGTGGATGGGA  989 FYB 0.49 TTGGACATCTCTAGTGTAGCTGCCA  990TRB@ 0.37 TTGGACATCTCTAGTGTAGCTGCCA  991 SEPT6 0.32GCCCCACTGGACAACACTGATTCCT  992 HA-1 0.48 GCCCCACTGGACAACACTGATTCCT  993DOCK2 0.33 TTGGACATCTCTAGTGTAGCTGCCA  994 CG018 0.37AAATGTTTCCTTGTGCCTGCTCCTG  995 CD3D 0.32 TCCTCCATCACCTGAAACACTGGAC  996T3JAM 0.41 TGCCTGCTCCTGTACTTGTCCTCAG  997 FNBP1 0.36TCCTGTACTTGTCCTCAGCTTGGGC  998 CD6 0.36 AAGCCTATACGTTTCTGTGGAGTAA  999ZAP70 0.36 TGGACCCCACTGGCTGAGAATCTGG 1000 LST1 0.31ACTTGTCCTCAGCTTGGGCTTCTTC 1001 GPR65 0.42 TTGGACATCTCTAGTGTAGCTGCCA 1002PRF1 0.41 GCCCCACTGGACAACACTGATTCCT 1003 AIF1 0.32GCCCCACTGGACAACACTGATTCCT 1004 FLJ20331 0.42 TCCTCCATCACCTGAAACACTGGAC1005 RAG2 0.31 CACCCAGCTGGTCCTGTGGATGGGA 1006 WDR45 0.37TCCTGTACTTGTCCTCAGCTTGGGC 1007 CD1E 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 1008CYFIP2 0.4 TCCTCCATCACCTGAAACACTGGAC 1009 TARP 0.36CACCCAGCTGGTCCTGTGGATGGGA 1010 TRIM 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 1011RPL10L 0.3 TTGGACATCTCTAGTGTAGCTGCCA 1012 GLTSCR2 0.46CACCCAGCTGGTCCTGTGGATGGGA 1013 GIMAP5 0.32 AAGCCTATACGTTTCTGTGGAGTAA1014 ARHGAP15 0.36 TGCCTGCTCCTGTACTTGTCCTCAG 1015 NOTCH1 0.34GCCCCACTGGACAACACTGATTCCT 1016 BIN2 0.36 TGGACCCCACTGGCTGAGAATCTGG 1017C13orf18 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 1018 CECR1 0.32TCCTGTACTTGTCCTCAGCTTGGGC 1019 BCL11B 0.32 TCCTTGTGCCTGCTCCTGTACTTGT1020 GIMAP6 0.3 TCCTTGTGCCTGCTCCTGTACTTGT 1021 STAG3 0.58TTGGACATCTCTAGTGTAGCTGCCA 1022 TM6SF1 0.31 TCCTGTACTTGTCCTCAGCTTGGGC1023 HSD17B7 0.32 GCCCCACTGGACAACACTGATTCCT 1024 UBASH3A 0.3ACTTGTCCTCAGCTTGGGCTTCTTC 1025 MGC5566 0.45 TCCTCCATCACCTGAAACACTGGAC1026 FLJ22457 0.39 AAGCCTATACGTTTCTGTGGAGTAA 1027 TPK1 0.33TGCCTGCTCCTGTACTTGTCCTCAG 1028 PHF11 0.3 AAATGTTTCCTTGTGCCTGCTCCTG 1029DKFZP434B0335 0.4 TCCTTGTGCCTGCTCCTGTACTTGT

TABLE 47 IL4-PR38 fusion protein biomarkers. SEQ ID Corre- NO Genelation Medianprobe 1030 MCL1 0.3 TCCTGCATCACCTGAAACACTGGAC 1031 DDX230.35 CACCCAGCTGGTCCTGTGGATGGGA 1032 JUNB 0.31 TGCCTGCTCCTGTACTTGTCCTCAG1033 ZFP36 0.33 CACCCAGCTGGTCCTGTGGATGGGA 1034 IFITM1 0.32ACTTGTCCTCAGCTTGGGCTTCTTC 1035 CKS1B 0.3 TGGACCCCACTGGCTGAGAATCTGG 1036SERPINA1 0.31 GCCCCACTGGACAACACTGATTCCT 1037 IL4R 0.3ACTTGTCCTCAGCTTGGGCTTCTTC 1038 CLDN3 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 1039ARL4A 0.33 AAATGTTTCCTTGTGCCTGCTCCTG 1040 HMMR 0.31TCCTTGTGCCTGCTCCTGTACTTGT 1041 FLJ12671 0.42 TCCTTGTGCCTGCTCCTGTACTTGT1042 ANKHD1 0.42 GCCCCACTGGACAACACTGATTCCT 1043 KIF2C 0.37ACTTGTCCTCAGCTTGGGCTTCTTC 1044 RPA3 0.34 CACCCAGCTGGTCCTGTGGATGGGA 1045MCCC2 0.34 TGCCTGCTCCTGTACTTGTCCTCAG 1046 CDH17 0.32TCCTTGTGCCTGCTCCTGTACTTGT 1047 LSM5 0.33 TTGGACATCTCTAGTGTAGCTGCCA 1048PRF1 0.32 GCCCCACTGGACAACACTGATTCCT 1049 ROD1 0.34TCCTCCATCACCTGAAACACTGGAC 1050 FLJ12666 0.37 TCCTCCATCACCTGAAACACTGGAC1051 SUV420H1 0.31 TTGGACATCTCTAGTGTAGCTGCCA 1052 MUC13 0.36TCCTCCATCACCTGAAACACTGGAC 1053 C13orf18 0.35 GCCCCACTGGACAACACTGATTCCT1054 CDCA8 0.35 TGCCTGCTCCTGTACTTGTCCTCAG

TABLE 48 Valproic acid (VPA) biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1055 STOM 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 1056 TNFAIP3 0.32TGGACCCCACTGGCTGAGAATCTGG 1057 ASNS 0.31 GCCCCACTGGACAACACTGATTCCT 1058GARS 0.37 TGCCTGCTCCTGTACTTGTCCTCAG 1059 CXCR4 0.32AAGCCTATACGTTTCTGTGGAGTAA 1060 EGLN3 0.31 TGGACCCCACTGGCTGAGAATCTGG 1061LBH 0.35 TCCTGTACTTGTCCTCAGCTTGGGC 1062 GDF15 0.3TGCCTGCTCCTGTACTTGTCCTCAG

TABLE 49 All-trans retinoic acid (ATRA) biomarkers. SEQ ID Corre- NOGene lation Medianprobe 1063 PPIB 0.31 AAGCCTATACGTTTCTGTGGAGTAA 1064ZFP36L2 0.48 AAGCCTATACGTTTCTGTGGAGTAA 1065 IFI30 0.46ACTTGTCCTCAGCTTGGGCTTCTTC 1066 USP7 0.35 TCCTCCATCACCTGAAACACTGGAC 1067SRM 0.43 TCCTCCATCACCTGAAACACTGGAC 1068 SH3BP5 0.32TGCCTGCTCCTGTACTTGTCCTCAG 1069 ALDOC 0.41 TTGGACATCTCTAGTGTAGCTGCCA 1070FADS2 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 1071 GUSB 0.38TTGGACATCTCTAGTGTAGCTGCCA 1072 PSCD1 0.48 TCCTGTACTTGTCCTCAGCTTGGGC 1073IQGAP2 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 1074 STS 0.34GCCCCACTGGACAACACTGATTCCT 1075 MFNG 0.36 TGGACCCCACTGGCTGAGAATCTGG 1076FLI1 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 1077 PIM2 0.35TGGACCCCACTGGCTGAGAATCTGG 1078 INPP4A 0.54 TCCTGTACTTGTCCTCAGCTTGGGC1079 LRMP 0.51 GCCCCACTGGACAACACTGATTCCT 1080 ICAM2 0.3AAATGTTTCCTTGTGCCTGCTCCTG 1081 EVI2A 0.33 CACCCAGCTGGTCCTGTGGATGGGA 1082MAL 0.46 AAATGTTTCCTTGTGCCTGCTCCTG 1083 BTN3A3 0.43TTGGACATCTCTAGTGTAGCTGCCA 1084 PTPN7 0.4 TTGGACATCTCTAGTGTAGCTGCCA 1085IL10RA 0.42 TTGGACATCTCTAGTGTAGCTGCCA 1086 SPI1 0.41AAGCCTATACGTTTCTGTGGAGTAA 1087 TRAF1 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 1088ITGB7 0.33 TCCTTGTGCCTGCTCCTGTACTTGT 1089 ARHGAP6 0.32TGGACCCCACTGGCTGAGAATCTGG 1090 MAP4K1 0.52 GCCCCACTGGACAACACTGATTCCT1091 CD28 0.34 AAGCCTATACGTTTCTGTGGAGTAA 1092 PTP4A3 0.3TCCTCCATCACCTGAAACACTGGAC 1093 LTB 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC 1094Clorf38 0.4 TGCCTGCTCCTGTACTTGTCCTCAG 1095 WBSCR22 0.53TCCTCCATCACCTGAAACACTGGAC 1096 CD8B1 0.35 TCCTCCATCACCTGAAACACTGGAC 1097LCP1 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC 1098 FLJ13052 0.31TCCTCCATCACCTGAAACACTGGAC 1099 MEF2C 0.71 TTGGACATCTCTAGTGTAGCTGCCA 1100PSCDBP 0.41 AAATGTTTCCTTGTGCCTGCTCCTG 1101 IL16 0.51TGGACCCCACTGGCTGAGAATCTGG 1102 SELPLG 0.53 TGCCTGCTCCTGTACTTGTCCTCAG1103 MAGEA9 0.6 AAATGTTTCCTTGTGCCTGCTCCTG 1104 LAIR1 0.43TCCTCCATCACCTGAAACACTGGAC 1105 TNFRSF25 0.53 TCCTCCATCACCTGAAACACTGGAC1106 EVI2B 0.42 ACTTGTCCTCAGCTTGGGCTTCTTC 1107 IGJ 0.37TCCTTGTGCCTGCTCCTGTACTTGT 1108 PDCD4 0.47 AAATGTTTCCTTGTGCCTGCTCCTG 1109RASA4 0.52 CACCCAGCTGGTCCTGTGGATGGGA 1110 HA-1 0.73AAGCCTATACGTTTCTGTGGAGTAA 1111 PLCL2 0.47 TCCTGTACTTGTCCTCAGCTTGGGC 1112RNASE6 0.31 AAGCCTATACGTTTCTGTGGAGTAA 1113 WBSCR20C 0.35TTGGACATCTCTAGTGTAGCTGCCA 1114 NUP210 0.36 AAGCCTATACGTTTCTGTGGAGTAA1115 RPL10L 0.39 ACTTGTCCTCAGCTTGGGCTTCTTC 1116 C11orf2 0.33TGGACCCCACTGGCTGAGAATCTGG 1117 CABC1 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 1118ARHGEF3 0.37 TCCTGTACTTGTCCTCAGCTTGGGC 1119 TAPBPL 0.42TGCCTGCTCCTGTACTTGTCCTCAG 1120 CHST12 0.35 AAATGTTTCCTTGTGCCTGCTCCTG1121 FKBP11 0.54 TGCCTGCTCCTGTACTTGTCCTCAG 1122 FLJ35036 0.42TTGGACATCTCTAGTGTAGCTGCCA 1123 MYLIP 0.38 CACCCAGCTGGTCCTGTGGATGGGA 1124TXNDC5 0.31 ACTTGTCCTCAGCTTGGGCTTGTTC 1125 PACAP 0.3TCCTCCATCACCTGAAACACTGGAC 1126 TOSO 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 1127PNAS-4 0.37 TGGACCCCACTGGCTGAGAATCTGG 1128 IL21R 0.57AAGCCTATACGTTTCTGTGGAGTAA 1129 TCF4 0.64 TCCTTGTGCCTGCTCCTGTACTTGT

TABLE 50 Cytoxan biomarkers. SEQ ID Corre- NO Gene lation Medianprobe1130 C6orf29 0.31 AAGCCTATACGTTTCTGTGGAGTAA 1131 TRIM31 0.31AAATGTTTCCTTGTGCCTGCTCCTG 1132 CD69 0.37 GCCCCACTGGACAACACTGATTCCT 1133LRRN3 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 1134 GPR35 0.41TCCTCCATCACCTGAAACACTGGAC 1135 CDW52 0.48 TTGGACATCTCTAGTGTAGCTGCCA

TABLE 51 Topotecan (Hycamtin) biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1136 K-ALPHA-1 0.32 AAGCCTATACGTTTCTGTGGAGTAA 1137 CSDA 0.32AAGCCTATACGTTTCTGTGGAGTAA 1138 UCHL1 0.32 TTGGACATCTCTAGTGTAGCTGCCA 1139NAP1L1 0.3 TCCTCCATCACCTGAAACACTGGAC 1140 ATP5G2 0.3TCCTGTACTTGTCCTCAGCTTGGGC 1141 HDGFRP3 0.3 AAGCCTATACGTTTCTGTGGAGTAA1142 IFI44 0.3 GCCCCACTGGACAACACTGATTCCT

TABLE 52 Suberoylanilide hydroxamic acid (SAHA, vorinostat, Zolinza)biomarkers. SEQ ID Corre- NO Gene lation Medianprobe 1143 NOL5A 0.35TCCTTGTGCCTGCTCCTGTACTTGT 1144 STOM 0.35 TGCCTGCTCCTGTACTTGTCCTCAG 1145SIAT1 0.36 AAATGTTTCCTTGTGCCTGCTCCTG 1146 CUGBP2 0.39GCCCCACTGGACAACACTGATTCCT 1147 GUSB 0.33 TGGACCCCACTGGCTGAGAATCTGG 1148ITM2A 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 1149 JARID2 0.32ACTTGTCCTCAGCTTGGGCTTCTTC 1150 RUNX3 0.32 CACCCAGCTGGTCCTGTGGATGGGA 1151ICAM2 0.35 TGCCTGCTCCTGTACTTGTCCTCAG 1152 PTPN7 0.37AAGCCTATACGTTTCTGTGGAGTAA 1153 VAV1 0.35 TTGGACATCTCTAGTGTAGCTGCCA 1154PTP4A3 0.42 AAGCCTATACGTTTCTGTGGAGTAA 1155 MCAM 0.35ACTTGTCCTCAGCTTGGGCTTCTTC 1156 MEF2C 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC 1157IDH3B 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 1158 RFP 0.31TCCTCCATCACCTGAAACACTGGAC 1159 SEPT6 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 1160SLC43A3 0.34 GCCCCACTGGACAACACTGATTCCT 1161 WBSCR20C 0.46TGGACCCCACTGGCTGAGAATCTGG 1162 SHMT2 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 1163GLTSCR2 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 1164 CABC1 0.33TCCTGTACTTGTCCTCAGCTTGGGC 1165 FLJ20859 0.42 ACTTGTCCTCAGCTTGGGCTTCTTC1166 FLJ20010 0.51 TCCTGTACTTGTCCTCAGCTTGGGC 1167 MGC10993 0.33TCCTTGTGCCTGCTCCTGTACTTGT 1168 FKBP11 0.31 TCCTCCATCACCTGAAACACTGGAC

TABLE 53 Depsipeptide (FR901228) biomarkers. SEQ ID Corre- NO Genelation Medianprobe 1169 ZFP36L2 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 1170TRIB2 0.35 TGCCTGCTCCTGTACTTGTCCTCAG 1171 LCP2 0.37ACTTGTCCTCAGCTTGGGCTTCTTC 1172 C6orf32 0.35 TGCCTGCTCCTGTACTTGTCCTCAG1173 IL16 0.34 CACCCAGCTGGTCCTGTGGATGGGA 1174 CACNA1G 0.31AAGCCTATACGTTTCTGTGGAGTAA 1175 SPDEF 0.31 GCCCCACTGGACAACACTGATTCCT 1176HAB1 0.39 TCCTCCATCACCTGAAACACTGGAC 1177 TOSO 0.31TGGACCCCACTGGCTGAGAATCTGG 1178 ARHGAP25 0.33 AAGCCTATACGTTTCTGTGGAGTAA

TABLE 54 Bortezomib biomarkers. SEQ ID Corre- NO Gene lation Medianprobe1179 PLEKHB2 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 1180 ARPC1B 0.32TGGACCCCACTGGCTGAGAATCTGG 1181 MX1 0.39 TCCTTGTGCCTGCTCCTGTACTTGT 1182CUGBP2 0.37 AAGCCTATACGTTTCTGTGGAGTAA 1183 IFI16 0.33AAGCCTATACGTTTCTGTGGAGTAA 1184 TNFRSF14 0.3 AAATGTTTCCTTGTGCCTGCTCCTG1185 SP110 0.39 TGGACCCCACTGGCTGAGAATCTGG 1186 ELF1 0.33TGGACCCCACTGGCTGAGAATCTGG 1187 LPXN 0.33 TCCTGTACTTGTCCTCAGCTTGGGC 1188IFRG28 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 1189 LEF1 0.33GCCCCACTGGACAACACTGATTCCT 1190 PYCARD 0.31 TCCTGTACTTGTCCTCAGCTTGGGC

TABLE 55 Leukeran biomarkers. SEQ ID Corre- NO Gene lation Medianprobe1191 SSRP1 0.31 GCCCCACTGGACAACACTGATTCCT 1192 ALDOC 0.36AAATGTTTCCTTGTGCCTGCTCCTG 1193 C1QR1 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 1194TTF1 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 1195 PRIM1 0.31GCCCCACTGGACAACACTGATTCCT 1196 USP34 0.38 TCCTCCATCACCTGAAACACTGGAC 1197TK2 0.33 TCCTGTACTTGTCCTCAGCTTGGGC 1198 GOLGIN-67 0.31TGCCTGCTCCTGTACTTGTCCTCAG 1199 NPD014 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC1200 KIAA0220 0.31 TCCTCCATCACCTGAAACACTGGAC 1201 SLC43A3 0.3TTGGACATCTCTAGTGTAGCTGCCA 1202 WBSCR20C 0.3 CACCCAGCTGGTCCTGTGGATGGGA1203 ICAM2 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 1204 TEX10 0.32TGGACCCCACTGGCTGAGAATCTGG 1205 CHD7 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC 1206SAMSN1 0.34 TTGGACATCTCTAGTGTAGCTGCCA 1207 TPRT 0.35ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 56 Fludarabine biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1208 HLA-E 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC 1209 BAT3 0.34TGCCTGCTCCTGTACTTGTCCTCAG 1210 ENO2 0.37 TGGACCCCACTGGCTGAGAATCTGG 1211UBE2L6 0.3 TCCTGTACTTGTCCTCAGCTTGGGC 1212 CUGBP2 0.35TGCCTGCTCCTGTACTTGTCCTCAG 1213 ITM2A 0.32 GCCCCACTGGACAACACTGATTCCT 1214PALM2-AKAP2 0.41 GCCCCACTGGACAACACTGATTCCT 1215 JARID2 0.33GCCCCACTGGACAACACTGATTCCT 1216 DGKA 0.33 TGGACCCCACTGGCTGAGAATCTGG 1217SLC7A6 0.4 AAGCCTATACGTTTCTGTGGAGTAA 1218 TFDP2 0.35AAATGTTTCCTTGTGCCTGCTCCTG 1219 ADA 0.41 TGCCTGCTCCTGTACTTGTCCTCAG 1220EDG1 0.33 TGCCTGCTCCTGTACTTGTCCTCAG 1221 ICAM2 0.46AAGCCTATACGTTTCTGTGGAGTAA 1222 PTPN7 0.33 TCCTCCATCACCTGAAACACTGGAC 1223CXorf9 0.35 AAGCCTATACGTTTCTGTGGAGTAA 1224 RHOH 0.31CACCCAGCTGGTCCTGTGGATGGGA 1225 MX2 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 1226ZNFN1A1 0.31 TCCTCCATCACCTGAAACACTGGAC 1227 COCH 0.33TGGACCCCACTGGCTGAGAATCTGG 1228 LCP2 0.34 TGGACCCCACTGGCTGAGAATCTGG 1229CLGN 0.31 TCCTCCATCACCTGAAACACTGGAC 1230 BNC1 0.38GCCCCACTGGACAACACTGATTCCT 1231 FLNC 0.3 TCCTGTACTTGTCCTCAGCTTGGGC 1232HLA-DRB3 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 1233 UCP2 0.34TGGACCCCACTGGCTGAGAATCTGG 1234 HLA-DRB1 0.3 GCCCCACTGGACAACACTGATTCCT1235 GATA3 0.37 TCCTTGTGCCTGCTCCTGTACTTGT 1236 PRKCQ 0.39AAATGTTTCCTTGTGCCTGCTCCTG 1237 SH2D1A 0.37 ACTTGTCCTCAGCTTGGGCTTCTTC1238 NFATC3 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 1239 TRB@ 0.35AAATGTTTCCTTGTGCCTGCTCCTG 1240 FNBP1 0.34 TCCTCCATCACCTGAAACACTGGAC 1241SEPT6 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 1242 NME4 0.32AAGCCTATACGTTTCTGTGGAGTAA 1243 DKFZP434C171 0.3TCCTTGTGCCTGCTCCTGTACTTGT 1244 ZC3HAV1 0.32 TCCTGTACTTGTCCTCAGCTTGGGC1245 SLC43A3 0.37 AAATGTTTCCTTGTGCCTGCTCCTG 1246 CD3D 0.31AAATGTTTCCTTGTGCCTGCTCCTG 1247 AIF1 0.35 TCCTCCATCACCTGAAACACTGGAC 1248SPTAN1 0.34 TCCTCCATCACCTGAAACACTGGAC 1249 CD1E 0.31TCCTTGTGCCTGCTCCTGTACTTGT 1250 TRIM 0.31 AAGCCTATACGTTTCTGTGGAGTAA 1251DATF1 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 1252 FHOD1 0.37TCCTGTACTTGTCCTCAGCTTGGGC 1253 ARHGAP15 0.3 CACCCAGCTGGTCCTGTGGATGGGA1254 STAG3 0.34 AAGCCTATACGTTTCTGTGGAGTAA 1255 SAP130 0.31TCCTGTACTTGTCCTCAGCTTGGGC 1256 CYLD 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 57 Vinblastine biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1257 CD99 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 58 Busulfan biomarkers. SEQ ID Corre- NO Gene lation Medianprobe1258 RPLP2 0.37 TCCTCCATCACCTGAAACACTGGAC 1259 BTG1 0.36ACTTGTCCTCAGCTTGGGCTTCTTC 1260 CSDA 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 1261ARHGDIB 0.38 AAGCCTATACGTTTCTGTGGAGTAA 1262 INSIG1 0.41TCCTCCATCACCTGAAACACTGGAC 1263 ALDOC 0.36 TTGGACATCTCTAGTGTAGCTGCCA 1264WASPIP 0.31 TCCTCCATCACCTGAAACACTGGAC 1265 C1QR1 0.46TCCTGTACTTGTCCTCAGCTTGGGC 1266 EDEM1 0.36 TGGACCCCACTGGCTGAGAATCTGG 1267SLA 0.35 TCCTTGTGCCTGCTCCTGTACTTGT 1268 MFNG 0.4TCCTTGTGCCTGCTCCTGTACTTGT 1269 GPSM3 0.75 GCCCCACTGGACAACACTGATTCCT 1270ADA 0.53 ACTTGTCCTCAGCTTGGGCTTCTTC 1271 LRMP 0.31TCCTGTACTTGTCCTCAGCTTGGGC 1272 EVI2A 0.52 TCCTCCATCACCTGAAACACTGGAC 1273FMNL1 0.45 ACTTGTCCTCAGCTTGGGCTTCTTC 1274 PTPN7 0.3ACTTGTCCTCAGCTTGGGCTTCTTC 1275 RHOH 0.39 ACTTGTCCTCAGCTTGGGCTTCTTC 1276ZNFN1A1 0.36 AAGCCTATACGTTTCTGTGGAGTAA 1277 CENTB1 0.33TTGGACATCTCTAGTGTAGCTGCCA 1278 MAP4K1 0.31 TGGACCCCACTGGCTGAGAATCTGG1279 CD28 0.51 TCCTGTACTTGTCCTCAGCTTGGGC 1280 SP110 0.38TCCTTGTGCCTGCTCCTGTACTTGT 1281 NAP1L1 0.31 TGCCTGCTCCTGTACTTGTCCTCAG1282 IFI16 0.35 TCCTCCATCACCTGAAACACTGGAC 1283 ARHGEF6 0.42AAATGTTTCCTTGTGCCTGCTCCTG 1284 SELPLG 0.45 TCCTGTACTTGTCCTCAGCTTGGGC1285 CD3Z 0.35 CACCCAGCTGGTCCTGTGGATGGGA 1286 SH2D1A 0.38CACCCAGCTGGTCCTGTGGATGGGA 1287 LAIR1 0.34 TGCCTGCTCCTGTACTTGTCCTCAG 1288RAFTLIN 0.36 GCCCCACTGGACAACACTGATTCCT 1289 HA-1 0.61ACTTGTCCTCAGCTTGGGCTTCTTC 1290 DOCK2 0.4 TGCCTGCTCCTGTACTTGTCCTCAG 1291CD3D 0.31 GCCCCACTGGACAACACTGATTCCT 1292 T3JAM 0.35ACTTGTCCTCAGCTTGGGCTTCTTC 1293 ZAP70 0.36 TGGACCCCACTGGCTGAGAATCTGG 1294GPR65 0.32 TCCTCCATCACCTGAAACACTGGAC 1295 CYFIP2 0.58CACCCAGCTGGTCCTGTGGATGGGA 1296 LPXN 0.34 TTGGACATCTCTAGTGTAGCTGCCA 1297RPL10L 0.41 TCCTGTACTTGTCCTCAGCTTGGGC 1298 GLTSCR2 0.33AAATGTTTCCTTGTGCCTGCTCCTG 1299 ARHGAP15 0.47 CACCCAGCTGGTCCTGTGGATGGGA1300 BCL11B 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 1301 TM6SF1 0.39AAGCCTATACGTTTCTGTGGAGTAA 1302 PACAP 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 1303TCF4 0.32 TGGACCCCACTGGCTGAGAATCTGG

TABLE 59 Dacarbazine biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1304 ARHGDIB 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 1305 ITM2A 0.4TCCTCCATCACCTGAAACACTGGAC 1306 SSBP2 0.33 CACCCAGCTGGTCCTGTGGATGGGA 1307PIM2 0.39 GCCCCACTGGACAACACTGATTCCT 1308 SELL 0.31GCCCCACTGGACAACACTGATTCCT 1309 ICAM2 0.43 TCCTGTACTTGTCCTCAGCTTGGGC 1310EVI2A 0.32 AAGCCTATACGTTTCTGTGGAGTAA 1311 MAL 0.32TTGGACATCTCTAGTGTAGCTGCCA 1312 PTPN7 0.34 ACTTGTCCTCAGCTTGGGCTTCTTC 1313ZNFN1A1 0.32 TCCTTGTGCCTGCTCCTGTACTTGT 1314 LCP2 0.3GCCCCACTGGACAACACTGATTCCT 1315 ARHGAP6 0.33 TGGACCCCACTGGCTGAGAATCTGG1316 CD28 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 1317 CD8B1 0.32TCCTCCATCACCTGAAACACTGGAC 1318 LCP1 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 1319NPD014 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 1320 CD69 0.32AAGCCTATACGTTTCTGTGGAGTAA 1321 NFATC3 0.32 AAGCCTATACGTTTCTGTGGAGTAA1322 TRB@ 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 1323 IGJ 0.33AAGCCTATACGTTTCTGTGGAGTAA 1324 SLC43A3 0.3 TTGGACATCTCTAGTGTAGCTGCCA1325 DOCK2 0.36 TCCTCCATCACCTGAAACACTGGAC 1326 FHOD1 0.33TGGACCCCACTGGCTGAGAATCTGG 1327 PACAP 0.31 AAGCCTATACGTTTCTGTGGAGTAA

TABLE 60 Oxaliplatin biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1328 RPL18 0.38 TTGGACATCTCTAGTGTAGCTGCCA 1329 RPL10A 0.32AAATGTTTCCTTGTGCCTGCTCCTG 1330 RPS3A 0.34 TGGACCCCACTGGCTGAGAATCTGG 1331EEF1B2 0.39 CACCCAGCTGGTCCTGTGGATGGGA 1332 GOT2 0.32AAGCCTATACGTTTCTGTGGAGTAA 1333 RPL13A 0.33 AAATGTTTCCTTGTGCCTGCTCCTG1334 RPS15 0.41 GCCCCACTGGACAACACTGATTCCT 1335 NOLSA 0.37TGCCTGCTCCTGTACTTGTCCTCAG 1336 RPLP2 0.36 TGCCTGCTCCTGTACTTGTCCTCAG 1337SLC9A3R1 0.43 TGGACCCCACTGGCTGAGAATCTGG 1338 E1F3S3 0.43GCCCCACTGGACAACACTGATTCCT 1339 MTHFD2 0.33 TGCCTGCTCCTGTACTTGTCCTCAG1340 IMPDH2 0.34 ACTTGTCCTCAGCTTGGGCTTCTTC 1341 ALDOC 0.44TGCCTGCTCCTGTACTTGTCCTCAG 1342 FABP5 0.33 CACCCAGCTGGTCCTGTGGATGGGA 1343ITM2A 0.35 TCCTTGTGCCTGCTCCTGTACTTGT 1344 PCK2 0.36ACTTGTCCTCAGCTTGGGCTTCTTC 1345 MFNG 0.33 GCCCCACTGGACAACACTGATTCCT 1346GCH1 0.37 TGGACCCCACTGGCTGAGAATCTGG 1347 PIM2 0.39CACCCAGCTGGTCCTGTGGATGGGA 1348 ADA 0.32 TCCTTGTGCCTGCTCCTGTACTTGT 1349ICAM2 0.31 TCCTCCATCACCTGAAACACTGGAC 1350 TTF1 0.47TTGGACATCTCTAGTGTAGCTGCCA 1351 MYB 0.36 TGCCTGCTCCTGTACTTGTCCTCAG 1352PTPN7 0.37 CACCCAGCTGGTCCTGTGGATGGGA 1353 RHOH 0.42TCCTCCATCACCTGAAACACTGGAC 1354 ZNFN1A1 0.39 ACTTGTCCTCAGCTTGGGCTTCTTC1355 PRIM1 0.36 TCCTTGTGCCTGCTCCTGTACTTGT 1356 FHIT 0.48TCCTCCATCACCTGAAACACTGGAC 1357 ASS 0.45 TGGACCCCACTGGCTGAGAATCTGG 1358SYK 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 1359 OXA1L 0.32TTGGACATCTCTAGTGTAGCTGCCA 1360 LCP1 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 1361DDX18 0.32 AAGCCTATACGTTTCTGTGGAGTAA 1362 NOLA2 0.35AAATGTTTCCTTGTGCCTGCTCCTG 1363 KIAA0922 0.41 TCCTCCATCACCTGAAACACTGGAC1364 PRKCQ 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 1365 NFATC3 0.32TCCTGTACTTGTCCTCAGCTTGGGC 1366 ANAPC5 0.34 TCCTCCATCACCTGAAACACTGGAC1367 TRB@ 0.4 TGGACCCCACTGGCTGAGAATCTGG 1368 CXCR4 0.32TCCTTGTGCCTGCTCCTGTACTTGT 1369 FNBP4 0.3 TCCTGTACTTGTCCTCAGCTTGGGC 1370SEPT6 0.53 TTGGACATCTCTAGTGTAGCTGCCA 1371 RPS2 0.35TCCTCCATCACCTGAAACACTGGAC 1372 MDN1 0.41 ACTTGTCCTCAGCTTGGGCTTCTTC 1373PCCB 0.32 AAGCCTATACGTTTCTGTGGAGTAA 1374 RASA4 0.33TGGACCCCACTGGCTGAGAATCTGG 1375 WBSCR20C 0.31 CACCCAGCTGGTCCTGTGGATGGGA1376 SFRS7 0.32 TTGGACATCTCTAGTGTAGCTGCCA 1377 WBSCR20A 0.3TGCCTGCTCCTGTACTTGTCCTCAG 1378 NUP210 0.43 TGGACCCCACTGGCTGAGAATCTGG1379 SHMT2 0.36 TCCTTGTGCCTGCTCCTGTACTTGT 1380 RPLP0 0.33TTGGACATCTCTAGTGTAGCTGCCA 1381 MAP4K1 0.31 CACCCAGCTGGTCCTGTGGATGGGA1382 HNRPA1 0.37 TCCTCCATCACCTGAAACACTGGAC 1383 CYFIP2 0.3GCCCCACTGGACAACACTGATTCCT 1384 RPL10L 0.32 TCGTCCATCACCTGAAACACTGGAC1385 GLTSCR2 0.39 TGGACCCCACTGGCTGAGAATCTGG 1386 MRPL16 0.38TCCTGTACTTGTCCTCAGCTTGGGC 1387 MRPS2 0.34 GCCCCACTGGACAACACTGATTCCT 1388FLJ12270 0.31 AAGCCTATACGTTTCTGTGGAGTAA 1389 CDK5RAP3 0.32TTGGACATCTCTAGTGTAGCTGCCA 1390 ARHGAP15 0.32 TCCTGTACTTGTCCTCAGCTTGGGC1391 CUTC 0.33 TCCTTGTGCCTGCTCCTGTACTTGT 1392 FKBP11 0.32ACTTGTCCTCAGCTTGGGCTTCTTC 1393 ADPGK 0.41 AAGCCTATACGTTTCTGTGGAGTAA 1394FLJ22457 0.32 GCCCCACTGGACAACACTGATTCCT 1395 PUS3 0.31TCCTTGTGCCTGCTCCTGTACTTGT 1396 PACAP 0.36 TGCCTGCTCCTGTACTTGTCCTCAG 1397CALML4 0.31 TCCTGTACTTGTCCTCAGCTTGGGC

TABLE 61 Hydroxyurea biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1398 CSDA 0.31 TCCTCCATCACCTGAAACACTGGAC 1399 INSIG1 0.38AAGCCTATACGTTTCTGTGGAGTAA 1400 UBE2L6 0.33 CACCCAGCTGGTCCTGTGGATGGGA1401 PRG1 0.36 GCCCCACTGGACAACACTGATTCCT 1402 ITM2A 0.3ACTTGTCCTCAGCTTGGGCTTCTTC 1403 DGKA 0.31 CACCCAGCTGGTCCTGTGGATGGGA 1404SLA 0.47 CACCCAGCTGGTCCTGTGGATGGGA 1405 PCBP2 0.51TGGACCCCACTGGCTGAGAATCTGG 1406 IL2RG 0.42 ACTTGTCCTCAGCTTGGGCTTCTTC 1407ALOX5AP 0.31 AAGCCTATACGTTTCTGTGGAGTAA 1408 PSMB9 0.33GCCCCACTGGACAACACTGATTCCT 1409 LRMP 0.36 TTGGACATCTCTAGTGTAGCTGCCA 1410ICAM2 0.31 TGGACCCCACTGGCTGAGAATCTGG 1411 PTPN7 0.36TCCTCCATCACCTGAAACACTGGAC 1412 CXorf9 0.38 TCCTTGTGCCTGCTCCTGTACTTGT1413 RHOH 0.41 TGCCTGCTCCTGTACTTGTCCTCAG 1414 ZNFN1A1 0.31AAATGTTTCCTTGTGCCTGCTCCTG 1415 CENTB1 0.36 TTGGACATCTCTAGTGTAGCTGCCA1416 LCP2 0.37 CACCCAGCTGGTCCTGTGGATGGGA 1417 STAT4 0.32GCCCCACTGGACAACACTGATTCCT 1418 CCR7 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 1419CD3G 0.33 AAATGTTTCCTTGTGCCTGCTCCTG 1420 SP110 0.32TCCTGTACTTGTCCTCAGCTTGGGC 1421 TNFAIP8 0.31 TCCTCCATCACCTGAAACACTGGAC1422 IFI16 0.4 TGGACCCCACTGGCTGAGAATCTGG 1423 CXCR4 0.37ACTTGTCCTCAGCTTGGGCTTCTTC 1424 ARHGEF6 0.37 TTGGACATCTCTAGTGTAGCTGCCA1425 SELPLG 0.3 TCCTCCATCACCTGAAACACTGGAC 1426 CD3Z 0.38TCCTCCATCACCTGAAACACTGGAC 1427 PRKCQ 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 1428SH2D1A 0.3 TCCTTGTGCCTGCTCCTGTACTTGT 1429 CD1A 0.31TTGGACATCTCTAGTGTAGCTGCCA 1430 NFATC3 0.33 TGGACCCCACTGGCTGAGAATCTGG1431 LAIR1 0.34 TCCTCCATCACCTGAAACACTGGAC 1432 TRB@ 0.3CACCCAGCTGGTCCTGTGGATGGGA 1433 SEPT6 0.34 CAGCCAGCTGGTCCTGTGGATGGGA 1434RAFTLIN 0.3 TCCTTGTGCCTGCTCCTGTACTTGT 1435 DOCK2 0.32TGGACCCCACTGGCTGAGAATCTGG 1436 CD3D 0.37 TGCCTGCTCCTGTACTTGTCCTCAG 1437CD6 0.42 AAGCCTATACGTTTCTGTGGAGTAA 1438 AIF1 0.4TGCCTGCTCCTGTACTTGTCCTCAG 1439 CD1E 0.41 GCCCCACTGGACAACACTGATTCCT 1440CYFIP2 0.35 TCCTGTACTTGTCCTCAGCTTGGGC 1441 TARP 0.38AAATGTTTCCTTGTGCCTGCTCCTG 1442 ADA 0.33 AAGCCTATACGTTTCTGTGGAGTAA 1443ARHGAP15 0.32 TGGACCCCACTGGCTGAGAATCTGG 1444 GIMAP6 0.34GCCCCACTGGACAACACTGATTCCT 1445 STAG3 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 1446FLJ22457 0.31 AAGCCTATACGTTTCTGTGGAGTAA 1447 PACAP 0.35AAGCCTATACGTTTCTGTGGAGTAA 1448 TCF4 0.4 TCCTGTACTTGTCCTCAGCTTGGGC

TABLE 62 Tegafur biomarkers. SEQ ID Corre- NO Gene lation Medianprobe1449 RPL11 0.31 GCCCCACTGGACAACACTGATTCCT 1450 RPL17 0.38TGCCTGCTCCTGTACTTGTCCTCAG 1451 ANAPC5 0.34 CACCCAGCTGGTCCTGTGGATGGGA1452 RPL13A 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 1453 STOM 0.37TCCTCCATCACCTGAAACACTGGAC 1454 TUFM 0.38 GCCCCACTGGACAACACTGATTCCT 1455SCARB1 0.35 TCCTGTACTTGTCCTCAGCTTGGGC 1456 FABP5 0.33CACCCAGCTGGTCCTGTGGATGGGA 1457 KIAA0711 0.35 TCCTTGTGCCTGCTCCTGTACTTGT1458 ILGR 0.33 TCCTCCATCACCTGAAACACTGGAC 1459 WBSCR22 0.3AAATGTTTCCTTGTGCCTGCTCCTG 1460 UCK2 0.4 TGCCTGCTCCTGTACTTGTCCTCAG 1461GZMB 0.3 AAGCCTATACGTTTCTGTGGAGTAA 1462 Clorf38 0.32CACCCAGCTGGTCCTGTGGATGGGA 1463 PCBP2 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 1464GPR65 0.44 TGCCTGCTCCTGTACTTGTCCTCAG 1465 GLTSCR2 0.38TCCTTGTGCCTGCTCCTGTACTTGT 1466 FKBP11 0.38 TGGACCCCACTGGCTGAGAATCTGG

TABLE 63 Daunorubicin biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1467 ALDOC 0.41 TGCCTGCTCCTGTACTTGTCCTCAG 1468 ITM2A 0.32GCCCCACTGGACAACACTGATTCCT 1469 SLA 0.41 TCCTTGTGCCTGCTCCTGTACTTGT 1470SSBP2 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 1471 IL2RG 0.31TGGACCCCACTGGCTGAGAATCTGG 1472 MFNG 0.47 TTGGACATCTCTAGTGTAGCTGCCA 1473SELL 0.33 TCCTCCATCACCTGAAACACTGGAC 1474 STC1 0.31AAATGTTTCCTTGTGCCTGCTCCTG 1475 LRMP 0.33 AAGCCTATACGTTTCTGTGGAGTAA 1476MYB 0.41 GCCCCACTGGACAACACTGATTCCT 1477 PTPN7 0.31AAATGTTTCCTTGTGCCTGCTCCTG 1478 CXorf9 0.38 TGGACCCCACTGGCTGAGAATCTGG1479 RHOH 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 1480 ZNFN1A1 0.36CACCCAGCTGGTCCTGTGGATGGGA 1481 CENTB1 0.37 TGGACCCCACTGGCTGAGAATCTGG1482 MAP4K1 0.32 TGGACCCCACTGGCTGAGAATCTGG 1483 CCR7 0.3TCCTGTACTTGTCCTCAGCTTGGGC 1484 CD3G 0.33 AAATGTTTCCTTGTGCCTGCTCCTG 1485CCR9 0.33 TGGACCCCACTGGCTGAGAATCTGG 1486 CBFA2T3 0.31CACCCAGCTGGTCCTGTGGATGGGA 1487 CXGR4 0.41 AAATGTTTCCTTGTGCCTGCTCCTG 1488ARHGEF6 0.4 TCCTGTACTTGTCCTCAGCTTGGGC 1489 SELPLG 0.45TCCTTGTGCCTGCTCCTGTACTTGT 1490 SEC31L2 0.38 TCCTGTACTTGTCCTCAGCTTGGGC1491 CD3Z 0.33 CACCCAGCTGGTCCTGTGGATGGGA 1492 SH2D1A 0.33TCCTGTACTTGTCCTCAGCTTGGGC 1493 CD1A 0.35 TGGACCCCACTGGCTGAGAATCTGG 1494SCN3A 0.33 CACCCAGCTGGTCCTGTGGATGGGA 1495 LAIR1 0.33TGCCTGCTCCTGTACTTGTCCTCAG 1496 TRB@ 0.3 AAATGTTTCCTTGTGCCTGCTCCTG 1497DOCK2 0.35 AAGCCTATACGTTTCTGTGGAGTAA 1498 WBSCR20C 0.38CACCCAGCTGGTCCTGTGGATGGGA 1499 CD3D 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 1500T3JAM 0.34 CACCCAGCTGGTCCTGTGGATGGGA 1501 CD6 0.33ACTTGTCCTCAGCTTGGGCTTCTTC 1502 ZAP70 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 1503GPR65 0.33 TCCTGTACTTGTCCTCAGCTTGGGC 1504 AIF1 0.3GCCCCACTGGACAACACTGATTCCT 1505 WDR45 0.3 TCCTCCATCACCTGAAACACTGGAC 1506CD1E 0.3 TCCTTGTGCCTGCTCCTGTACTTGT 1507 CYFIP2 0.39AAGCCTATACGTTTCTGTGGAGTAA 1508 TARP 0.38 TTGGACATCTCTAGTGTAGCTGCCA 1509TRIM 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 1510 ARHGAP15 0.37ACTTGTCCTCAGCTTGGGCTTCTTC 1511 NOTCH1 0.39 AAGCCTATACGTTTCTGTGGAGTAA1512 STAG3 0.35 AAGCCTATACGTTTCTGTGGAGTAA 1513 UBASH3A 0.31TGCCTGCTCCTGTACTTGTCCTCAG 1514 MGC5566 0.33 TGCCTGCTCCTGTACTTGTCCTCAG1515 PACAP 0.33 TCCTTGTGCCTGCTCCTGTACTTGT

TABLE 64 Bleomycin biomarkers. SEQ ID Corre- NO Gene lation Medianprobe1516 PFN1 0.32 CACCCAGCTGGTCCTGTGGATGGGA 1517 CALU 0.32ACTTGTCCTCAGCTTGGGCTTCTTC 1518 ZYX 0.34 CACCCAGCTGGTCCTGTGGATGGGA 1519PSMD2 0.36 GCCCCACTGGACAACACTGATTCCT 1520 RAP1B 0.32TCCTGTACTTGTCCTCAGCTTGGGC 1521 EPAS1 0.35 TCCTGTACTTGTCCTCAGCTTGGGC 1522PGAM1 0.36 GCCCCACTGGACAACACTGATTCCT 1523 STAT1 0.38TGCCTGCTCCTGTACTTGTCCTCAG 1524 CKAP4 0.38 GCCCCACTGGACAACACTGATTCCT 1525DUSP1 0.32 TCCTGTACTTGTCCTCAGCTTGGGC 1526 RCN1 0.32TCCTCCATCACCTGAAACACTGGAC 1527 UCHL1 0.44 TGGACCCCACTGGCTGAGAATCTGG 1528ITGA5 0.33 AAATGTTTCCTTGTGCCTGCTCCTG 1529 NFKBIA 0.32TGCCTGCTCCTGTACTTGTCCTCAG 1530 LAMB1 0.4 GCCCCACTGGACAACACTGATTCCT 1531TGFBI 0.37 TTGGACATCTCTAGTGTAGCTGCCA 1532 FHL1 0.31GCCCCACTGGACAACACTGATTCCT 1533 GJA1 0.32 TCCTCCATCACCTGAAACACTGGAC 1534PRG1 0.33 CACCCAGCTGGTCCTGTGGATGGGA 1535 EXT1 0.35CACCCAGCTGGTCCTGTGGATGGGA 1536 MVP 0.32 TCCTGTACTTGTCCTCAGCTTGGGC 1537NNMT 0.38 TGGACCCCACTGGCTGAGAATCTGG 1538 TAP1 0.37TCCTCCATCACCTGAAACACTGGAC 1539 CRIM1 0.41 TGGACCCCACTGGCTGAGAATCTGG 1540PLOD2 0.36 GCCCCACTGGACAACACTGATTCCT 1541 RPS19 0.34TCCTGTACTTGTCCTCAGCTTGGGC 1542 AXL 0.43 GCCCCACTGGACAACACTGATTCCT 1543PALM2-AKAP2 0.42 TCCTCCATCACCTGAAACACTGGAC 1544 IL8 0.32TCCTGTACTTGTCCTCAGCTTGGGC 1545 LOXL2 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 1546PAPSS2 0.31 CACCCAGCTGGTCCTGTGGATGGGA 1547 CAV1 0.31TCCTTGTGCCTGCTCCTGTACTTGT 1548 F2R 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC 1549PSMB9 0.38 CACCCAGCTGGTCCTGTGGATGGGA 1550 LOX 0.36TGGACCCCACTGGCTGAGAATCTGG 1551 Clorf29 0.36 TCCTGTACTTGTCCTCAGCTTGGGC1552 STC1 0.32 TTGGACATCTCTAGTGTAGCTGCCA 1553 LIF 0.34TCCTTGTGCCTGCTCCTGTACTTGT 1554 KCNJ8 0.46 GCCCCACTGGACAACACTGATTCCT 1555SMAD3 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 1556 HPCAL1 0.45AAATGTTTCCTTGTGCCTGCTCCTG 1557 WNT5A 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 1558BDNF 0.33 TGCCTGCTCCTGTACTTGTCCTCAG 1559 TNFRSF1A 0.38TCCTGTACTTGTCCTCAGCTTGGGC 1560 NCOR2 0.45 CACCCAGCTGGTCCTGTGGATGGGA 1561FLNC 0.44 TTGGACATCTCTAGTGTAGCTGCCA 1562 HMGA2 0.41AAATGTTTCCTTGTGCCTGCTCCTG 1563 HLA-B 0.42 AAGCCTATACGTTTCTGTGGAGTAA 1564FLOT1 0.3 AAATGTTTCCTTGTGCCTGCTCCTG 1565 PTRF 0.36CACCCAGCTGGTCCTGTGGATGGGA 1566 IFI16 0.32 TCCTTGTGCCTGCTCCTGTACTTGT 1567MGC4083 0.34 TCCTCCATCACCTGAAACACTGGAC 1568 TNFRSF10B 0.4ACTTGTCCTCAGCTTGGGCTTCTTC 1569 PNMA2 0.38 TCCTGTACTTGTCCTCAGCTTGGGC 1570TFPI 0.32 TCCTTGTGCCTGCTCCTGTACTTGT 1571 CLECSF2 0.33TGCCTGCTCCTGTACTTGTCCTCAG 1572 SP110 0.34 GCCCCACTGGACAACACTGATTCCT 1573PLAUR 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC 1574 ASPH 0.42TCCTTGTGCCTGCTCCTGTACTTGT 1575 FSCN1 0.38 TGCCTGCTCCTGTACTTGTCCTCAG 1576HIC 0.46 TCCTCCATCACCTGAAACACTGGAC 1577 HLA-C 0.34TGGACCCCACTGGCTGAGAATCTGG 1578 COL6A1 0.34 TCCTCCATCACCTGAAACACTGGAC1579 IL6ST 0.45 AAATGTTTCCTTGTGCCTGCTCCTG 1580 IFITM3 0.36GCCCCACTGGACAACACTGATTCCT 1581 MAP1B 0.31 TCCTCCATCACCTGAAACACTGGAC 1582FLJ46603 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC 1583 RAFTLIN 0.32GCCCCACTGGACAACACTGATTCCT 1584 FTL 0.37 CACCCAGCTGGTCCTGTGGATGGGA 1585KIAA0877 0.43 TCCTCCATCACCTGAAACACTGGAC 1586 MT1E 0.41TGGACCCCACTGGCTGAGAATCTGG 1587 CDC10 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 1588ZNF258 0.31 AAATGTTTCCTTGTGCCTGCTCCTG 1589 BCAT1 0.39TTGGACATCTCTAGTGTAGCTGCCA 1590 IFI44 0.36 AAATGTTTCCTTGTGCCTGCTCCTG 1591SOD2 0.36 GCCCCACTGGACAACACTGATTCCT 1592 TMSB10 0.33TCCTCCATCACCTGAAACACTGGAC 1593 FLJ10350 0.3 TTGGACATCTCTAGTGTAGCTGCCA1594 Clorf24 0.34 CACCCAGCTGGTCCTGTGGATGGGA 1595 EFHD2 0.36AAATGTTTCCTTGTGCCTGCTCCTG 1596 RPS27L 0.33 AAGCCTATACGTTTCTGTGGAGTAA1597 TNFRSF12A 0.43 CACCCAGCTGGTCCTGTGGATGGGA 1598 FAD104 0.38TTGGACATCTCTAGTGTAGCTGCCA 1599 RAB7L1 0.58 ACTTGTCCTCAGCTTGGGCTTCTTC1600 NME7 0.36 TTGGACATCTCTAGTGTAGCTGCCA 1601 TMEM22 0.34TTGGACATCTCTAGTGTAGCTGCCA 1602 TPK1 0.31 GCCCCACTGGACAACACTGATTCCT 1603ELK3 0.36 TGGACCCCACTGGCTGAGAATCTGG 1604 CYLD 0.3AAGCCTATACGTTTCTGTGGAGTAA 1605 AMIGO2 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC1606 ADAMTS1 0.43 ACTTGTCCTCAGCTTGGGCTTCTTC 1607 ACTB 0.36ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 65 Estramustine biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1608 HSPCB 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 1609 LDHA 0.42TGCCTGCTCCTGTACTTGTCCTCAG 1610 TM4SF7 0.32 TCCTGTACTTGTCCTCAGCTTGGGC

TABLE 66 Chlorambucil biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1611 CSDA 0.33 TGGACCCCACTGGCTGAGAATCTGG 1612 INSIG1 0.32TCCTTGTGCCTGCTCCTGTACTTGT 1613 UBE2L6 0.39 TGGACCCCACTGGCTGAGAATCTGG1614 PRG1 0.37 TCCTTGTGCCTGCTCCTGTACTTGT 1615 ITM2A 0.3GCCCCACTGGACAACACTGATTCCT 1616 DGKA 0.38 TCCTTGTGCCTGCTCCTGTACTTGT 1617TFDP2 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 1618 SLA 0.32TCCTCCATCACCTGAAACACTGGAC 1619 IL2RG 0.44 AAGCCTATACGTTTCTGTGGAGTAA 1620ALOX5AP 0.45 GCCCCACTGGACAACACTGATTCCT 1621 GPSM3 0.34TTGGACATCTCTAGTGTAGCTGCCA 1622 PSMB9 0.36 ACTTGTCCTCAGCTTGGGCTTCTTC 1623SELL 0.42 TGCCTGCTCCTGTACTTGTCCTCAG 1624 ADA 0.35ACTTGTCCTCAGCTTGGGCTTCTTC 1625 EDG1 0.33 AAATGTTTCCTTGTGCCTGCTCCTG 1626FMNL1 0.3 TCCTCCATCACCTGAAACACTGGAC 1627 PTPN7 0.5TCCTTGTGCCTGCTCCTGTACTTGT 1628 CXorf9 0.41 TGGACCCCACTGGCTGAGAATCTGG1629 RHOH 0.35 TTGGACATCTCTAGTGTAGCTGCCA 1630 ZNFN1A1 0.32TCCTTGTGCCTGCTCCTGTACTTGT 1631 CENTB1 0.47 TCCTGTACTTGTCCTCAGCTTGGGC1632 LCP2 0.37 TCCTCCATCACCTGAAACACTGGAC 1633 CD1D 0.36AAGCCTATACGTTTCTGTGGAGTAA 1634 STAT4 0.31 AAATGTTTCCTTGTGCCTGCTCCTG 1635VAV1 0.35 AAATGTTTCCTTGTGCCTGCTCCTG 1636 MAP4K1 0.36TTGGACATCTCTAGTGTAGCTGCCA 1637 CCR7 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 1638PDE4C 0.42 GCCCCACTGGACAACACTGATTCCT 1639 CD3G 0.41AAGCCTATACGTTTCTGTGGAGTAA 1640 CCR9 0.43 AAGCCTATACGTTTCTGTGGAGTAA 1641SP110 0.43 TTGGACATCTCTAGTGTAGCTGCCA 1642 TNFAIP8 0.48TTGGACATCTCTAGTGTAGCTGCCA 1643 LCP1 0.31 AAATGTTTCCTTGTGCCTGCTCCTG 1644IFI16 0.5 TCCTCCATCACCTGAAACACTGGAC 1645 CXCR4 0.37ACTTGTCCTCAGCTTGGGCTTCTTC 1646 ARHGEF6 0.37 ACTTGTCCTCAGCTTGGGCTTCTTC1647 SELPLG 0.43 TTGGACATCTCTAGTGTAGCTGCCA 1648 SEC31L2 0.32TGGACCCCACTGGCTGAGAATCTGG 1649 CD3Z 0.3 AAGCCTATACGTTTCTGTGGAGTAA 1650PRKCQ 0.31 GGCCCACTGGACAACACTGATTCCT 1651 SH2D1A 0.47ACTTGTCCTCAGCTTGGGCTTCTTC 1652 GZMB 0.48 TGGACCCCACTGGCTGAGAATCTGG 1653CD1A 0.3 AAGCCTATACGTTTCTGTGGAGTAA 1654 LAIR1 0.32TTGGACATCTCTAGTGTAGCTGCCA 1655 AF1Q 0.41 TTGGACATCTCTAGTGTAGCTGCCA 1656TRB@ 0.35 TCCTCCATCACCTGAAACACTGGAC 1657 SEPT6 0.35TGGACCCCACTGGCTGAGAATCTGG 1658 DOCK2 0.39 AAGCCTATACGTTTCTGTGGAGTAA 1659RPS19 0.41 TTGGACATCTCTAGTGTAGCTGCCA 1660 CD3D 0.4TTGGACATCTCTAGTGTAGCTGCCA 1661 T3JAM 0.32 TGGACCCCACTGGCTGAGAATCTGG 1662FNBP1 0.31 GCCCCACTGGACAACACTGATTCCT 1663 CD6 0.33TGGACCCCACTGGCTGAGAATCTGG 1664 ZAP70 0.52 CACCCAGCTGGTCCTGTGGATGGGA 1665LST1 0.34 AAATGTTTCCTTGTGCCTGCTCCTG 1666 BCAT1 0.35AAGCCTATACGTTTCTGTGGAGTAA 1667 PRF1 0.4 AAGCCTATACGTTTCTGTGGAGTAA 1668AIF1 0.3 TTGGACATCTCTAGTGTAGCTGCCA 1669 RAG2 0.38TGGACCCCACTGGCTGAGAATCTGG 1670 CD1E 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC 1671CYFIP2 0.38 TTGGACATCTCTAGTGTAGCTGCCA 1672 TARP 0.3TGGACCCCACTGGCTGAGAATCTGG 1673 TRIM 0.36 CACCCAGCTGGTCCTGTGGATGGGA 1674GLTSCR2 0.37 TCCTCCATCACCTGAAACACTGGAC 1675 GIMAP5 0.3ACTTGTCCTCAGCTTGGGCTTCTTC 1676 ARHGAP15 0.32 AAGCCTATACGTTTCTGTGGAGTAA1677 NOTCH1 0.31 CACCCAGCTGGTCCTGTGGATGGGA 1678 BCL11B 0.3TCCTTGTGCCTGCTCCTGTACTTGT 1679 GIMAP6 0.34 TTGGACATCTCTAGTGTAGCTGCCA1680 STAG3 0.4 TCCTGTACTTGTCCTCAGCTTGGGC 1681 TM6SF1 0.39TTGGACATCTCTAGTGTAGCTGCCA 1682 UBASH3A 0.37 TCCTGTACTTGTCCTCAGCTTGGGC1683 MGC5566 0.36 CACCCAGCTGGTCCTGTGGATGGGA 1684 FLJ22457 0.31TCCTCCATCACCTGAAACACTGGAC 1685 TPK1 0.33 AAATGTTTCCTTGTGCCTGCTCCTG

TABLE 67 Mechlorethamine biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1686 PRG1 0.37 GCCCCACTGGACAACACTGATTCCT 1687 SLC2A3 0.35ACTTGTCCTCAGCTTGGGCTTCTTC 1688 RPS19 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC 1689PSMB10 0.34 TGCCTGCTCCTGTACTTGTCCTCAG 1690 ITM2A 0.33TGCCTGCTCCTGTACTTGTCCTCAG 1691 DGKA 0.37 TGCCTGCTCCTGTACTTGTCCTCAG 1692SEMA4D 0.34 TCCTCCATCACCTGAAACACTGGAC 1693 SLA 0.33TGCCTGCTCCTGTACTTGTCCTCAG 1694 IL2RG 0.3 TGGACCCCACTGGCTGAGAATCTGG 1695MFNG 0.42 AAGCCTATACGTTTCTGTGGAGTAA 1696 ALOX5AP 0.31AAGCCTATACGTTTCTGTGGAGTAA 1697 GPSM3 0.34 AAGCCTATACGTTTCTGTGGAGTAA 1698PSMB9 0.36 ACTTGTCCTCAGCTTGGGCTTCTTC 1699 SELL 0.34CACCCAGCTGGTCCTGTGGATGGGA 1700 ADA 0.35 AAATGTTTCCTTGTGCCTGCTCCTG 1701FMNL1 0.4 CACCCAGCTGGTCCTGTGGATGGGA 1702 MYB 0.34TGGACCCCACTGGCTGAGAATCTGG 1703 PTPN7 0.43 AAGCCTATACGTTTCTGTGGAGTAA 1704CXorf9 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 1705 RHOH 0.33TTGGACATCTCTAGTGTAGCTGCCA 1706 ZNFN1A1 0.31 TCCTCCATCACCTGAAACACTGGAC1707 CENTB1 0.43 TCCTCCATCACCTGAAACACTGGAC 1708 FXYD2 0.35TTGGACATCTCTAGTGTAGCTGCCA 1709 CD1D 0.4 TTGGACATCTCTAGTGTAGCTGCCA 1710STAT4 0.44 TTGGACATCTCTAGTGTAGCTGCCA 1711 MAP4K1 0.34GCCCCACTGGACAACACTGATTCCT 1712 CCR7 0.39 TGGACCCCACTGGCTGAGAATCTGG 1713PDE4C 0.33 TCCTTGTGCCTGCTCCTGTACTTGT 1714 CD3G 0.4GCCCCACTGGACAACACTGATTCCT 1715 CCR9 0.34 TGGACCCCACTGGCTGAGAATCTGG 1716SP110 0.31 AAATGTTTCCTTGTGCCTGCTCCTG 1717 TK2 0.33TCCTGTACTTGTCCTCAGCTTGGGC 1718 TNFAIP8 0.34 GCCCCACTGGACAACACTGATTCCT1719 NAP1L1 0.35 TCCTGTACTTGTCCTCAGCTTGGGC 1720 SELPLG 0.35TCCTGTACTTGTCCTCAGCTTGGGC 1721 SEC31L2 0.38 TGCCTGCTCCTGTACTTGTCCTCAG1722 CD3Z 0.44 TTGGACATCTCTAGTGTAGCTGCCA 1723 PRKCQ 0.37TCCTGTACTTGTCCTCAGCTTGGGC 1724 SH2D1A 0.41 GCCCCACTGGACAACACTGATTCCT1725 GZMB 0.43 TGGACCCCACTGGCTGAGAATCTGG 1726 CD1A 0.39TGGACCCCACTGGCTGAGAATCTGG 1727 LAIR1 0.35 TGGACCCCACTGGCTGAGAATCTGG 1728TRB@ 0.33 TTGGACATCTCTAGTGTAGCTGCCA 1729 SEPT6 0.3CACCCAGCTGGTCCTGTGGATGGGA 1730 DOCK2 0.34 TGGACCCCACTGGCTGAGAATCTGG 1731CG018 0.33 TGGACCCCACTGGCTGAGAATCTGG 1732 WBSCR20C 0.34TCCTGTACTTGTCCTCAGCTTGGGC 1733 CD3D 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 1734CD6 0.32 AAGCCTATACGTTTCTGTGGAGTAA 1735 LST1 0.33TTGGACATCTCTAGTGTAGCTGCCA 1736 GPR65 0.42 AAGCCTATACGTTTCTGTGGAGTAA 1737PRF1 0.34 CACCCAGCTGGTCCTGTGGATGGGA 1738 ALMS1 0.41TCCTGTACTTGTCCTCAGCTTGGGC 1739 AIF1 0.31 GCCCCACTGGACAACACTGATTCCT 1740CD1E 0.31 CACCCAGCTGGTCCTGTGGATGGGA 1741 CYFIP2 0.33GCCCCACTGGACAACACTGATTCCT 1742 TARP 0.31 AAATGTTTCCTTGTGCCTGCTCCTG 1743GLTSCR2 0.31 AAGCCTATACGTTTCTGTGGAGTAA 1744 FLJ12270 0.34TGGACCCCACTGGCTGAGAATCTGG 1745 ARHGAP15 0.33 GCCCCACTGGACAACACTGATTCCT1746 NAP1L2 0.32 GCCCCACTGGACAACACTGATTCCT 1747 CECR1 0.34TCCTTGTGCCTGCTCCTGTACTTGT 1748 GIMAP6 0.35 TCCTGTACTTGTCCTCAGCTTGGGC1749 STAG3 0.33 CACCCAGCTGGTCCTGTGGATGGGA 1750 TM6SF1 0.3CACCCAGCTGGTCCTGTGGATGGGA 1751 C15orf25 0.36 TTGGACATCTCTAGTGTAGCTGCCA1752 MGC5566 0.32 TCCTGTACTTGTCCTCAGCTTGGGC 1753 FLJ22457 0.34AAATGTTTCCTTGTGCCTGCTCCTG 1754 ET 0.32 CACCCAGCTGGTCCTGTGGATGGGA 1755TPK1 0.34 CACCCAGCTGGTCCTGTGGATGGGA 1756 PHF11 0.36TTGGACATCTCTAGTGTAGCTGCCA

TABLE 68 Streptozocin biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1757 PGK1 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 1758 SCD 0.31TGGACCCCACTGGCTGAGAATCTGG 1759 INSIG1 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 1760IGBP1 0.39 TCCTCCATCACCTGAAACACTGGAC 1761 TNFAIP3 0.31TCCTCCATCACCTGAAACACTGGAC 1762 TNFSF10 0.31 CACCCAGCTGGTCCTGTGGATGGGA1763 ABCA1 0.34 TGCCTGCTCCTGTACTTGTCCTCAG 1764 AGA 0.31TGGACCCCACTGGCTGAGAATCTGG 1765 ABCA8 0.31 CACCCAGCTGGTCCTGTGGATGGGA 1766DBC1 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 1767 PTGER2 0.32ACTTGTCCTCAGCTTGGGCTTCTTC 1768 UGT1A3 0.32 TCCTCCATCACCTGAAACACTGGAC1769 C10orf10 0.3 CACCCAGCTGGTCCTGTGGATGGGA 1770 TM4SF13 0.34TGGACCCCACTGGCTGAGAATCTGG 1771 CGI-90 0.31 TCCTTGTGCCTGCTCCTGTACTTGT1772 LXN 0.31 AAGCCTATACGTTTCTGTGGAGTAA 1773 DNAJC12 0.35TTGGACATCTCTAGTGTAGCTGCCA 1774 HIPK2 0.31 CACCCAGCTGGTCCTGTGGATGGGA 1775C9orf95 0.36 ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 69 Carmustine biomarkers. SEQ ID Corre- NO Gene lation Medianprobe1776 RPLP2 0.34 TGCCTGCTCCTGTACTTGTCCTCAG 1777 CD99 0.31ACTTGTCCTCAGCTTGGGCTTCTTC 1778 IFITM1 0.36 TCCTCCATCACCTGAAACACTGGAC1779 INSIG1 0.31 TCCTCCATCACCTGAAACACTGGAC 1780 ALDOC 0.4TGCCTGCTCCTGTACTTGTCCTCAG 1781 ITM2A 0.33 TCCTTGTGCCTGCTCCTGTACTTGT 1782SERPINA1 0.39 TTGGACATCTCTAGTGTAGCTGCCA 1783 C1QR1 0.35AAGCCTATACGTTTCTGTGGAGTAA 1784 STAT5A 0.39 TTGGACATCTCTAGTGTAGCTGCCA1785 INPP5D 0.44 TCCTTGTGCCTGCTCCTGTACTTGT 1786 SATB1 0.36AAATGTTTCCTTGTGCCTGCTCCTG 1787 VPS16 0.31 AAATGTTTCCTTGTGCCTGCTCCTG 1788SLA 0.37 TCCTGTACTTGTCCTCAGCTTGGGC 1789 IL2RG 0.45TCCTCCATCACCTGAAACACTGGAC 1790 MFNG 0.33 TCCTCCATCACCTGAAACACTGGAC 1791SELL 0.38 AAGCCTATACGTTTCTGTGGAGTAA 1792 LRMP 0.41GCCCCACTGGACAACACTGATTCCT 1793 ICAM2 0.54 TCCTCCATCACCTGAAACACTGGAC 1794MYB 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 1795 PTPN7 0.3TGCCTGCTCCTGTACTTGTCCTCAG 1796 ARHGAP25 0.42 TTGGACATCTCTAGTGTAGCTGCCA1797 LCK 0.41 TGGACCCCACTGGCTGAGAATCTGG 1798 CXorf9 0.35TGGACCCCACTGGCTGAGAATCTGG 1799 RHOH 0.41 AAATGTTTCCTTGTGCCTGCTCCTG 1800ZNFN1A1 0.37 TGCCTGCTCCTGTACTTGTCCTCAG 1801 CENTB1 0.59ACTTGTCCTCAGCTTGGGCTTCTTC 1802 ADD2 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 1803LCP2 0.33 TTGGACATCTCTAGTGTAGCTGCCA 1804 SFI1 0.39TGCCTGCTCCTGTACTTGTCCTCAG 1805 DBT 0.42 ACTTGTCCTCAGCTTGGGCTTCTTC 1806GZMA 0.34 CACCCAGCTGGTCCTGTGGATGGGA 1807 CD2 0.36TGGACCCCACTGGCTGAGAATCTGG 1808 BATF 0.38 ACTTGTCCTCAGCTTGGGCTTCTTC 1809HIST1H4C 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 1810 ARHGAP6 0.4TCCTCCATCACCTGAAACACTGGAC 1811 VAV1 0.42 TGGACCCCACTGGCTGAGAATCTGG 1812MAP4K1 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 1813 CCR7 0.31TCCTTGTGCCTGCTCCTGTACTTGT 1814 PDE4C 0.57 TCCTCCATCACCTGAAACACTGGAC 1815CD3G 0.44 AAGCCTATACGTTTCTGTGGAGTAA 1816 CCR9 0.37AAATGTTTCCTTGTGCCTGCTCCTG 1817 SP140 0.48 TCCTGTACTTGTCCTCAGCTTGGGC 1818TK2 0.31 TGGACCCCACTGGCTGAGAATCTGG 1819 LCP1 0.38TCCTCCATCACCTGAAACACTGGAC 1820 IFI16 0.34 GCCCCACTGGACAACACTGATTCCT 1821CXCR4 0.42 GCCCCACTGGACAACACTGATTCCT 1822 ARHGEF6 0.45AAATGTTTCCTTGTGCCTGCTCCTG 1823 PSCDBP 0.42 TCCTGTACTTGTCCTCAGCTTGGGC1824 SELPLG 0.52 TGGACCCCACTGGCTGAGAATCTGG 1825 SEC31L2 0.42TCCTGTACTTGTCCTCAGCTTGGGC 1826 CD3Z 0.34 TCCTCCATCACCTGAAACACTGGAC 1827PRKCQ 0.46 TCCTTGTGCCTGCTCCTGTACTTGT 1828 SH2D1A 0.46TGCCTGCTCCTGTACTTGTCCTCAG 1829 GZMB 0.55 TTGGACATCTCTAGTGTAGCTGCCA 1830CD1A 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 1831 GATA2 0.41TTGGACATCTCTAGTGTAGCTGCCA 1832 LY9 0.54 TCCTCCATCACCTGAAACACTGGAC 1833LAIR1 0.3 TTGGACATGTCTAGTGTAGCTGCCA 1834 TRB@ 0.33TCCTCCATCACCTGAAACACTGGAC 1835 SEPT6 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC 1836HA-1 0.32 TCCTCCATCACCTGAAACACTGGAC 1837 SLC43A3 0.32TCCTGTACTTGTCCTCAGCTTGGGC 1838 DOCK2 0.31 TCCTCCATCACCTGAAACACTGGAC 1839CG018 0.42 ACTTGTCCTCAGCTTGGGCTTCTTC 1840 MLC1 0.33TGCCTGCTCCTGTACTTGTCCTCAG 1841 CD3D 0.35 TCCTGTACTTGTCCTCAGCTTGGGC 1842T3JAM 0.34 CACCCAGCTGGTCCTGTGGATGGGA 1843 CD6 0.43TCCTGTACTTGTCCTCAGCTTGGGC 1844 ZAP70 0.43 GCCCCACTGGACAACACTGATTCCT 1845DOK2 0.3 TCCTGTACTTGTCCTCAGCTTGGGC 1846 LST1 0.36TCCTGTACTTGTCCTCAGCTTGGGC 1847 GPR65 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 1848PRF1 0.32 TCCTTGTGCCTGCTCCTGTACTTGT 1849 ALMS1 0.38TTGGACATCTCTAGTGTAGCTGCCA 1850 AIF1 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 1851PRDX2 0.48 GCCCCACTGGACAACACTGATTCCT 1852 FLJ12151 0.36AAATGTTTCCTTGTGCCTGCTCCTG 1853 FBXW12 0.37 TGCCTGCTCCTGTACTTGTCCTCAG1854 CD1E 0.34 AAGCCTATACGTTTCTGTGGAGTAA 1855 CYFIP2 0.3TCCTTGTGCCTGCTCCTGTACTTGT 1856 TARP 0.33 TCCTGTACTTGTCCTCAGCTTGGGC 1857TRIM 0.38 CACCCAGCTGGTCCTGTGGATGGGA 1858 RPL10L 0.43AAATGTTTCCTTGTGCCTGCTCCTG 1859 GLTSCR2 0.43 CACCCAGCTGGTCCTGTGGATGGGA1860 CKIP-1 0.33 TCCTTGTGCCTGCTCCTGTACTTGT 1861 NRN1 0.3TCCTTGTGCCTGCTCCTGTACTTGT 1862 ARHGAP15 0.4 TCCTCCATCACCTGAAACACTGGAC1863 NOTCH1 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 1864 PSCD4 0.4CACCCAGCTGGTCCTGTGGATGGGA 1865 C13orf18 0.31 AAGCCTATACGTTTCTGTGGAGTAA1866 BCL11B 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC 1867 GIMAP6 0.33ACTTGTCCTCAGCTTGGGCTTCTTC 1868 STAG3 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 1869NARF 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 1870 TM6SF1 0.48TCCTCCATCACCTGAAACACTGGAC 1871 C15orf25 0.32 TCCTGTACTTGTCCTCAGCTTGGGC1872 FLJ11795 0.35 GCCCCACTGGACAACACTGATTCCT 1873 SAMSN1 0.37GCCCCACTGGACAACACTGATTCCT 1874 UBASH3A 0.4 TCCTGTACTTGTCCTCAGCTTGGGC1875 PACAP 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 1876 LEF1 0.3CACCCAGCTGGTCCTGTGGATGGGA 1877 IL21R 0.34 AAGCCTATACGTTTCTGTGGAGTAA 1878TCF4 0.41 GCCCCACTGGACAACACTGATTCCT 1879 DKFZP434B0335 0.33TCCTGTACTTGTCCTCAGCTTGGGC

TABLE 70 Lomustine biomarkers. SEQ ID Corre- NO Gene lation Medianprobe1880 RPS15 0.43 TCCTGTACTTGTCCTCAGCTTGGGC 1881 INSIG1 0.31TGGACCCCACTGGCTGAGAATCTGG 1882 ALDOC 0.39 TGCCTGCTCCTGTACTTGTCCTCAG 1883ITM2A 0.32 TCCTCCATCACCTGAAACACTGGAC 1884 C1QR1 0.33TGCCTGCTCCTGTACTTGTCCTCAG 1885 STAT5A 0.37 TGCCTGCTCCTGTACTTGTCCTCAG1886 INPP5D 0.32 TCCTGTACTTGTCCTCAGCTTGGGC 1887 VPS16 0.32TGCCTGCTCCTGTACTTGTCCTCAG 1888 SLA 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 1889USP20 0.41 ACTTGTCCTCAGCTTGGGCTTCTTC 1890 IL2RG 0.31TCCTGTACTTGTCCTCAGCTTGGGC 1891 MFNG 0.4 ACTTGTCCTCAGCTTGGGCTTCTTC 1892LRMP 0.43 GCCCCACTGGACAACACTGATTCCT 1893 EVI2A 0.35ACTTGTCCTCAGCTTGGGCTTCTTC 1894 PTPN7 0.35 TCCTTGTGCCTGCTCCTGTACTTGT 1895ARHGAP25 0.39 TCCTGTACTTGTCCTCAGCTTGGGC 1896 RHOH 0.31AAGCCTATACGTTTCTGTGGAGTAA 1897 ZNFN1A1 0.31 TCCTGTACTTGTCCTCAGCTTGGGC1898 CENTB1 0.35 TCCTGTACTTGTCCTCAGCTTGGGC 1899 LCP2 0.41TGGACCCCACTGGCTGAGAATCTGG 1900 SPI1 0.35 TGCCTGCTCCTGTACTTGTCCTCAG 1901ARHGAP6 0.33 TTGGACATCTCTAGTGTAGCTGCCA 1902 MAP4K1 0.34CACCCAGCTGGTCCTGTGGATGGGA 1903 CCR7 0.35 TCCTCCATCACCTGAAACACTGGAC 1904LY96 0.35 GCCCCACTGGACAACACTGATTCCT 1905 C6orf32 0.32ACTTGTCCTCAGCTTGGGCTTCTTC 1906 MAGEA1 0.31 AAATGTTTCCTTGTGCCTGCTCCTG1907 SP140 0.35 TTGGACATCTCTAGTGTAGCTGCCA 1908 LCP1 0.36TCCTCCATCACCTGAAACACTGGAC 1909 IFI16 0.39 TGCCTGCTCCTGTACTTGTCCTCAG 1910ARHGEF6 0.33 TCCTCCATCACCTGAAACACTGGAC 1911 PSCDBP 0.43AAGCCTATACGTTTCTGTGGAGTAA 1912 SELPLG 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC 1913CD3Z 0.35 AAGCCTATACGTTTCTGTGGAGTAA 1914 PRKCQ 0.4TCCTTGTGCCTGCTCCTGTACTTGT 1915 GZMB 0.31 AAGCCTATACGTTTCTGTGGAGTAA 1916LAIR1 0.38 TGGACCCCACTGGCTGAGAATCTGG 1917 SH2D1A 0.36TCCTGTACTTGTCCTCAGCTTGGGC 1918 TRB@ 0.39 TTGGACATCTCTAGTGTAGCTGCCA 1919RFP 0.35 TGCCTGCTCCTGTACTTGTCCTCAG 1920 SEPT6 0.41TCCTCCATCACCTGAAACACTGGAC 1921 HA-1 0.43 TCCTGTACTTGTCCTCAGCTTGGGC 1922SLC43A3 0.4 ACTTGTCCTCAGCTTGGGCTTCTTC 1923 CD3D 0.32TCCTTGTGCCTGCTCCTGTACTTGT 1924 T3JAM 0.3 TGGACCCCACTGGCTGAGAATCTGG 1925GPR65 0.34 GCCCCACTGGACAACACTGATTCCT 1926 PRF1 0.36TGCCTGCTCCTGTACTTGTCCTCAG 1927 AIF1 0.33 TGGACCCCACTGGCTGAGAATCTGG 1928LPXN 0.38 AAATGTTTCCTTGTGCCTGCTCCTG 1929 RPL10L 0.3TGGACCCCACTGGCTGAGAATCTGG 1930 SITPEC 0.36 CACCCAGCTGGTCCTGTGGATGGGA1931 ARHGAP15 0.33 TGGACCCCACTGGCTGAGAATCTGG 1932 C13orf18 0.32TCCTGTACTTGTCCTCAGCTTGGGC 1933 NARF 0.35 TGGACCCCACTGGCTGAGAATCTGG 1934TM6SF1 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 1935 PACAP 0.31AAGCCTATACGTTTCTGTGGAGTAA 1936 TCF4 0.33 TCCTTGTGCCTGCTCCTGTACTTGT

TABLE 71 Mercaptopurine biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 1937 SSRP1 0.31 GCCCCACTGGACAACACTGATTCCT 1938 ALDOC 0.36AAATGTTTCCTTGTGCCTGCTCCTG 1939 C1QRl 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 1940TTF1 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 1941 PRIM1 0.31GCCCCACTGGACAACACTGATTCCT 1942 USP34 0.38 TCCTCCATCACCTGAAACACTGGAC 1943TK2 0.33 TCCTGTACTTGTCCTCAGCTTGGGC 1944 GOLGIN-67 0.31TGCCTGCTCCTGTACTTGTCCTCAG 1945 N2D014 0.35 ACTTGTCCTCAGCTTGGGCTTCTTC1946 KIAA0220 0.31 TCCTCCATCACCTGAAACACTGGAC 1947 SLC43A3 0.3TTGGACATCTCTAGTGTAGCTGCCA 1948 WBSCR20C 0.3 CACCCAGCTGGTCCTGTGGATGGGA1949 ICAM2 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 1950 TEX10 0.32TGGACCCCACTGGCTGAGAATCTGG 1951 CHD7 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC 1952SAMSN1 0.34 TTGGACATCTCTAGTGTAGCTGCCA 1953 TPRT 0.35ACTTGTCCTCAGCTTGGGCTTCTTC

TABLE 72 Teniposide biomarkers. SEQ ID Corre- NO Gene lation Medianprobe1954 CD99 0.35 TGCCTGCTCCTGTACTTGTCCTCAG 1955 INSIG1 0.35AAGCCTATACGTTTCTGTGGAGTAA 1956 PRG1 0.36 TGCCTGCTCCTGTACTTGTCCTCAG 1957ALDOC 0.3 ACTTGTCCTCAGCTTGGGCTTCTTC 1958 ITM2A 0.33AAGCCTATACGTTTCTGTGGAGTAA 1959 SLA 0.43 GCCCCACTGGACAACACTGATTCCT 1960SSBP2 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 1961 IL2RG 0.37AAATGTTTCCTTGTGCCTGCTCCTG 1962 MFNG 0.32 TTGGACATCTCTAGTGTAGCTGCCA 1963ALOX5AP 0.32 TCCTCCATCACCTGAAACACTGGAC 1964 C1orf29 0.3TCCTCCATCACCTGAAACACTGGAC 1965 SELL 0.33 CACCCAGCTGGTCCTGTGGATGGGA 1966STC1 0.47 TGGACCCCACTGGCTGAGAATCTGG 1967 LRMP 0.33TCCTCCATCACCTGAAACACTGGAC 1968 MYB 0.33 TGCCTGCTCCTGTACTTGTCCTCAG 1969PTPN7 0.34 AAGCCTATACGTTTCTGTGGAGTAA 1970 CXorf9 0.42TTGGACATCTCTAGTGTAGCTGCCA 1971 RHOH 0.31 AAGCCTATACGTTTCTGTGGAGTAA 1972ZNFN1A1 0.34 CACCCAGCTGGTCCTGTGGATGGGA 1973 CENTB1 0.37TGGACCCCACTGGCTGAGAATCTGG 1974 ADD2 0.31 TGCCTGCTCCTGTACTTGTCCTCAG 1975CD1D 0.37 ACTTGTCCTCAGCTTGGGCTTCTTC 1976 BATF 0.32TCCTGTACTTGTCCTCAGCTTGGGC 1977 MAP4K1 0.3 GCCCCACTGGACAACACTGATTCCT 1978CCR7 0.48 TCCTGTACTTGTCCTCAGCTTGGGC 1979 PDE4C 0.33TGGACCCCACTGGCTGAGAATCTGG 1980 CD3G 0.33 TTGGACATCTCTAGTGTAGCTGCCA 1981CCR9 0.36 ACTTGTCCTCAGCTTGGGCTTCTTC 1982 SP110 0.34AAATGTTTCCTTGTGCCTGCTCCTG 1983 TNFAIP8 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC1984 NAP1L1 0.32 AAGCCTATACGTTTCTGTGGAGTAA 1985 CXCR4 0.31ACTTGTCCTCAGCTTGGGCTTCTTC 1986 ARHGEF6 0.31 TCCTGTACTTGTCCTCAGCTTGGGC1987 GATA3 0.36 TCCTGTACTTGTCCTCAGCTTGGGC 1988 SELPLG 0.38AAGCCTATACGTTTCTGTGGAGTAA 1989 SEC31L2 0.46 TGGACCCCACTGGCTGAGAATCTGG1990 CD3Z 0.35 GCCCCACTGGACAACACTGATTCCT 1991 SH2D1A 0.45AAATGTTTCCTTGTGCCTGCTCCTG 1992 GZMB 0.35 TCCTTGTGCCTGCTCCTGTACTTGT 1993CD1A 0.45 GCCCCACTGGACAACACTGATTCCT 1994 SCN3A 0.31TCCTTGTGCCTGCTCCTGTACTTGT 1995 LAIR1 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 1996AF1Q 0.3 TCCTCCATCACCTGAAACACTGGAC 1997 TRB@ 0.32AAGCCTATACGTTTCTGTGGAGTAA 1998 DOCK2 0.33 TCCTGTACTTGTCCTCAGCTTGGGC 1999MLC1 0.31 TCCTCCATCACCTGAAACACTGGAC 2000 CD3D 0.31TGGACCCCACTGGCTGAGAATCTGG 2001 T3JAM 0.31 ACTTGTCCTCAGCTTGGGCTTCTTC 2002CD6 0.38 TGCCTGCTCCTGTACTTGTCCTCAG 2003 ZAP70 0.34TCCTCCATCACCTGAAACACTGGAC 2004 IFI44 0.37 TCCTTGTGCCTGCTCCTGTACTTGT 2005GPR65 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 2006 PRF1 0.34TCCTCCATCACCTGAAACACTGGAC 2007 AIF1 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 2008WDR45 0.41 GCCCCACTGGACAACACTGATTCCT 2009 CD1E 0.31AAGCCTATACGTTTCTGTGGAGTAA 2010 CYFIP2 0.32 TGGACCCCACTGGCTGAGAATCTGG2011 TARP 0.42 CACCCAGCTGGTCCTGTGGATGGGA 2012 TRIM 0.33TGGACCCCACTGGCTGAGAATCTGG 2013 ARHGAP15 0.38 AAGCCTATACGTTTCTGTGGAGTAA2014 NOTCH1 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 2015 STAG3 0.32GCCCCACTGGACAACACTGATTCCT 2016 NARF 0.31 AAGCCTATACGTTTCTGTGGAGTAA 2017TM6SF1 0.33 GCCCCACTGGACAACACTGATTCCT 2018 UBASH3A 0.33TCCTGTACTTGTCCTCAGCTTGGGC 2019 MGC5566 0.31 AGTTGTCCTCAGCTTGGGCTTCTTC

TABLE 73 Dactinomycin biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 2020 ALDOC 0.37 GCCCCACTGGACAACACTGATTCCT 2021 C1QR1 0.36TGGACCCCACTGGCTGAGAATCTGG 2022 SLA 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 2023WBSCR20A 0.31 AAGCCTATACGTTTCTGTGGAGTAA 2024 MFNG 0.3ACTTGTCCTCAGCTTGGGCTTCTTC 2025 SELL 0.3 GCCCCACTGGACAACACTGATTCCT 2026MYB 0.36 TTGGACATCTCTAGTGTAGCTGCCA 2027 RHOH 0.32TCCTTGTGCCTGCTCCTGTACTTGT 2028 ZNFN1A1 0.3 AAATGTTTCCTTGTGCCTGCTCCTG2029 LCP2 0.3 CACCCAGCTGGTCCTGTGGATGGGA 2030 MAP4K1 0.34AAGCCTATACGTTTCTGTGGAGTAA 2031 CBFA2T3 0.35 TCCTTGTGCCTGCTCCTGTACTTGT2032 LCP1 0.32 GCCCCACTGGACAACACTGATTCCT 2033 SELPLG 0.33ACTTGTCCTCAGCTTGGGCTTCTTC 2034 CD3Z 0.35 GCCCCACTGGACAACACTGATTCCT 2035LAIR1 0.33 TGGACCCCACTGGCTGAGAATCTGG 2036 WBSCR20C 0.3AAGCCTATACGTTTCTGTGGAGTAA 2037 CD3D 0.35 CACCCAGCTGGTCCTGTGGATGGGA 2038GPR65 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 2039 ARHGAP15 0.32TCCTCCATCACCTGAAACACTGGAC 2040 FLJ10178 0.36 TCCTTGTGCCTGCTCCTGTACTTGT2041 NARF 0.35 TCCTCCATCACCTGAAACACTGGAC 2042 PUS3 0.32TCCTGTACTTGTCCTCAGCTTGGGC

TABLE 74 Tretinoin biomarkers. SEQ ID Corre- NO Gene lation Medianprobe2043 PPIB 0.31 AAGCCTATACGTTTCTGTGGAGTAA 2044 ZFP36L2 0.48AAGCCTATACGTTTCTGTGGAGTAA 2045 IFI30 0.46 ACTTGTCCTCAGCTTGGGCTTCTTC 2046USP7 0.35 TCCTCCATCACCTGAAACACTGGAC 2047 SRM 0.43TCCTCCATCACCTGAAACACTGGAC 2048 SH3BP5 0.32 TGCCTGCTCCTGTACTTGTCCTCAG2049 ALDOC 0.41 TTGGACATCTCTAGTGTAGCTGCCA 2050 FADS2 0.33ACTTGTCCTCAGCTTGGGCTTCTTC 2051 GUSB 0.38 TTGGACATCTCTAGTGTAGCTGCCA 2052PSCD1 0.48 TCCTGTACTTGTCCTCAGCTTGGGC 2053 IQGAP2 0.34TCCTGTACTTGTCCTCAGCTTGGGC 2054 STS 0.34 GCCCCACTGGACAACACTGATTCCT 2055MFNG 0.36 TGGACCCCACTGGCTGAGAATCTGG 2056 FLI1 0.33ACTTGTCCTCAGCTTGGGCTTCTTC 2057 PIM2 0.35 TGGACCCCACTGGCTGAGAATCTGG 2058INPP4A 0.54 TCCTGTACTTGTCCTCAGCTTGGGC 2059 LRMP 0.51GCCCCACTGGACAACACTGATTCCT 2060 ICAM2 0.3 AAATGTTTCCTTGTGCCTGCTCCTG 2061EVI2A 0.33 CACCCAGCTGGTCCTGTGGATGGGA 2062 MAL 0.46AAATGTTTCCTTGTGCCTGCTCCTG 2063 BTN3A3 0.43 TTGGACATCTCTAGTGTAGCTGCCA2064 PTPN7 0.4 TTGGACATCTCTAGTGTAGCTGCCA 2065 IL10RA 0.42TTGGACATCTCTAGTGTAGCTGCCA 2066 SPI1 0.41 AAGCCTATACGTTTCTGTGGAGTAA 2067TRAF1 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 2068 ITGB7 0.33TCCTTGTGCCTGCTCCTGTACTTGT 2069 ARHGAP6 0.32 TGGACCCCACTGGCTGAGAATCTGG2070 MAP4K1 0.52 GCCCCACTGGACAACACTGATTCCT 2071 CD28 0.34AAGCCTATACGTTTCTGTGGAGTAA 2072 PTP4A3 0.3 TCCTCCATCACCTGAAACACTGGAC 2073LTB 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC 2074 C1orf38 0.4TGCCTGCTCCTGTACTTGTCCTCAG 2075 WBSCR22 0.53 TCCTCCATCACCTGAAACACTGGAC2076 CD8B1 0.35 TCCTCCATCACCTGAAACACTGGAC 2077 LCP1 0.35ACTTGTCCTCAGCTTGGGCTTCTTC 2078 FLJ13052 0.31 TCCTCCATCACCTGAAACACTGGAC2079 MEF2C 0.71 TTGGACATCTCTAGTGTAGCTGCCA 2080 PSCDBP 0.41AAATGTTTCCTTGTGCCTGCTCCTG 2081 IL16 0.51 TGGACCCCACTGGCTGAGAATCTGG 2082SELPLG 0.53 TGCCTGCTCCTGTACTTGTCCTCAG 2083 MAGEA9 0.6AAATGTTTCCTTGTGCCTGCTCCTG 2084 LAIR1 0.43 TCCTCCATCACCTGAAACACTGGAC 2085TNFRSF25 0.53 TCCTCCATCACCTGAAACACTGGAC 2086 EVI2B 0.42ACTTGTCCTCAGCTTGGGCTTCTTC 2087 IGJ 0.37 TCCTTGTGCCTGCTCCTGTACTTGT 2088PDCD4 0.47 AAATGTTTCCTTGTGCCTGCTCCTG 2089 RASA4 0.52CACCCAGCTGGTCCTGTGGATGGGA 2090 HA-1 0.73 AAGCCTATACGTTTCTGTGGAGTAA 2091PLCL2 0.47 TCCTGTACTTGTCCTCAGCTTGGGC 2092 RNASE6 0.31AAGCCTATACGTTTCTGTGGAGTAA 2093 WBSCR20C 0.35 TTGGACATCTCTAGTGTAGCTGCCA2094 NUP210 0.36 AAGCCTATACGTTTCTGTGGAGTAA 2095 RPL10L 0.39ACTTGTCCTCAGCTTGGGCTTCTTC 2096 C11orf2 0.33 TGGACCCCACTGGCTGAGAATCTGG2097 CABC1 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 2098 ARHGEF3 0.37TCCTGTACTTGTCCTCAGCTTGGGC 2099 TAPBPL 0.42 TGCCTGCTCCTGTACTTGTCCTCAG2100 CHST12 0.35 AAATGTTTCCTTGTGCCTGCTCCTG 2101 FKBP11 0.54TGCCTGCTCCTGTACTTGTCCTCAG 2102 FLJ35036 0.42 TTGGACATCTCTAGTGTAGCTGCCA2103 MYLIP 0.38 CACCCAGCTGGTCCTGTGGATGGGA 2104 TXNDC5 0.31ACTTGTCCTCAGCTTGGGCTTCTTC 2105 PACAP 0.3 TCCTCCATCACCTGAAACACTGGAC 2106TOSO 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 2107 PNAS-4 0.37TGGACCCCACTGGCTGAGAATCTGG 2108 IL21R 0.57 AAGCCTATACGTTTCTGTGGAGTAA 2109TCF4 0.64 TCCTTGTGCCTGCTCCTGTACTTGT

TABLE 75 Ifosfamide biomarkers. SEQ ID Corre- NO Gene lation Medianprobe2110 ARHGDIB 0.36 TGGACCCCACTGGCTGAGAATCTGG 2111 ZFP36L2 0.45TGGACCCCACTGGCTGAGAATCTGG 2112 ITM2A 0.39 AAGCCTATACGTTTCTGTGGAGTAA 2113LGALS9 0.54 AAATGTTTCCTTGTGCCTGCTCCTG 2114 INPP5D 0.53TCCTGTACTTGTCCTCAGCTTGGGC 2115 SATB1 0.35 TTGGACATCTCTAGTGTAGCTGCCA 2116TFDP2 0.32 AAGCCTATACGTTTCTGTGGAGTAA 2117 IL2RG 0.32TGCCTGCTCCTGTACTTGTCCTCAG 2118 CD48 0.5 ACTTGTCCTCAGCTTGGGCTTCTTC 2119SELL 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC 2120 ADA 0.32TGCCTGCTCCTGTACTTGTCCTCAG 2121 LRMP 0.34 GCCCCACTGGACAACACTGATTCCT 2122RIMS3 0.37 AAGCCTATACGTTTCTGTGGAGTAA 2123 LCK 0.37TCCTGTACTTGTCCTCAGCTTGGGC 2124 CXorf9 0.4 CACCCAGCTGGTCCTGTGGATGGGA 2125RHOH 0.3 GCCCCACTGGACAACACTGATTCCT 2126 ZNFN1A1 0.31TTGGACATCTCTAGTGTAGCTGCCA 2127 LCP2 0.37 TCCTGTACTTGTCCTCAGCTTGGGC 2128CD1D 0.49 TCCTCCATCACCTGAAACACTGGAC 2129 CD2 0.42CACCCAGCTGGTCCTGTGGATGGGA 2130 ZNF91 0.45 AAATGTTTCCTTGTGCCTGCTCCTG 2131MAP4K1 0.32 TCCTTGTGCCTGCTCCTGTACTTGT 2132 CCR7 0.44TTGGACATCTCTAGTGTAGCTGCCA 2133 IGLL1 0.43 TGCCTGCTCCTGTACTTGTCCTCAG 2134CD3G 0.3 TCCTCCATCACCTGAAACACTGGAC 2135 ZNF430 0.31ACTTGTCCTCAGCTTGGGCTTCTTC 2136 CCR9 0.31 TTGGACATCTCTAGTGTAGCTGCCA 2137CXCR4 0.37 ACTTGTCCTCAGCTTGGGCTTCTTC 2138 KIAA0922 0.31AAGCCTATACGTTTCTGTGGAGTAA 2139 TARP 0.31 GCCCCACTGGACAACACTGATTCCT 2140FYN 0.35 TCCTGTACTTGTCCTCAGCTTGGGC 2141 SH2D1A 0.34TTGGACATCTCTAGTGTAGCTGCCA 2142 CD1A 0.31 AAGCCTATACGTTTCTGTGGAGTAA 2143LST1 0.33 TTGGACATCTCTAGTGTAGCTGCCA 2144 LAIR1 0.36ACTTGTCCTCAGCTTGGGCTTCTTC 2145 TRB@ 0.34 TGGACCCCACTGGCTGAGAATCTGG 2146SEPT6 0.39 TTGGACATCTCTAGTGTAGCTGCCA 2147 CD3D 0.37TCCTCCATCACCTGAAACACTGGAC 2148 CD6 0.32 AAATGTTTCCTTGTGCCTGCTCCTG 2149AIF1 0.34 TGCCTGCTCCTGTACTTGTCCTCAG 2150 CD1E 0.31TCCTGTACTTGTCCTCAGCTTGGGC 2151 TRIM 0.32 TCCTGTACTTGTCCTCAGCTTGGGC 2152GLTSCR2 0.34 TCCTGTACTTGTCCTCAGCTTGGGC 2153 ARHGAP15 0.33TCCTGTACTTGTCCTCAGCTTGGGC 2154 BIN2 0.33 TGCCTGCTCCTGTACTTGTCCTCAG 2155SH3TC1 0.32 TGGACCCCACTGGCTGAGAATCTGG 2156 CECR1 0.36TCCTCCATCACCTGAAACACTGGAC 2157 BCL11B 0.38 TCCTCCATCACCTGAAACACTGGAC2158 GIMAP6 0.32 GCCCCACTGGACAACACTGATTCCT 2159 STAG3 0.46TTGGACATCTCTAGTGTAGCTGCCA 2160 GALNT6 0.32 ACTTGTCCTCAGCTTGGGCTTCTTC2161 MGC5566 0.49 TCCTTGTGCCTGCTCCTGTACTTGT 2162 PACAP 0.48TCCTGTACTTGTCCTCAGCTTGGGC 2163 LEF1 0.4 TGCCTGCTCCTGTACTTGTCCTCAG

TABLE 76 Tamoxifen biomarkers. SEQ ID Corre- NO Gene lation Medianprobe2164 MLP 0.33 TCCTGTACTTGTCCTCAGCTTGGGC 2165 GLUL 0.33TCCTTGTGCCTGCTCCTGTACTTGT 2166 SLC9A3R1 0.37 CACCCAGCTGGTCCTGTGGATGGGA2167 ZFP36L2 0.33 TTGGACATCTCTAGTGTAGCTGCCA 2168 INSIG1 0.31TCCTCCATCACCTGAAACACTGGAC 2169 TBL1X 0.36 TCCTGTACTTGTCCTCAGCTTGGGC 2170NDUFAB1 0.43 AAATGTTTCCTTGTGCCTGCTCCTG 2171 EBP 0.31TGGACCCCACTGGCTGAGAATCTGG 2172 TRIM14 0.43 TTGGACATCTCTAGTGTAGCTGCCA2173 SRPK2 0.41 GCCCCACTGGACAACACTGATTCCT 2174 PMM2 0.4AAATGTTTCCTTGTGCCTGCTCCTG 2175 CLDN3 0.41 AAGCCTATACGTTTCTGTGGAGTAA 2176GCH1 0.34 TTGGACATCTCTAGTGTAGCTGCCA 2177 IDI1 0.34AAATGTTTCCTTGTGCCTGCTCCTG 2178 TTF1 0.46 TCCTTGTGCCTGCTCCTGTACTTGT 2179MYB 0.39 CACCCAGCTGGTCCTGTGGATGGGA 2180 RASGRP1 0.32CACCCAGCTGGTCCTGTGGATGGGA 2181 HIST1H3H 0.38 TGGACCCCACTGGCTGAGAATCTGG2182 CBFA2T3 0.34 AAATGTTTCCTTGTGCCTGCTCCTG 2183 SRRM2 0.43GCCCCACTGGACAACACTGATTCCT 2184 ANAPC5 0.31 TCCTGTACTTGTCCTCAGCTTGGGC2185 MBD4 0.5 TCCTGTACTTGTCCTCAGCTTGGGC 2186 GATA3 0.32TCCTCCATCACCTGAAACACTGGAC 2187 HIST1H2BG 0.32 AAGCCTATACGTTTCTGTGGAGTAA2188 RAB14 0.31 TGGACCCCACTGGCTGAGAATCTGG 2189 PIK3R1 0.36AAGCCTATACGTTTCTGTGGAGTAA 2190 MGC50853 0.37 CACCCAGCTGGTCCTGTGGATGGGA2191 ELF1 0.35 GCCCCACTGGACAACACTGATTCCT 2192 ZRF1 0.32TCCTTGTGCCTGCTCCTGTACTTGT 2193 ZNF394 0.31 AAATGTTTCCTTGTGCCTGCTCCTG2194 S100A14 0.39 AAATGTTTCCTTGTGCCTGCTCCTG 2195 SLC6A14 0.31CACCCAGCTGGTCCTGTGGATGGGA 2196 GALNT6 0.37 TCCTCCATCACCTGAAACACTGGAC2197 SPDEF 0.44 AAATGTTTCCTTGTGCCTGCTCCTG 2198 TPRT 0.5AAGCCTATACGTTTCTGTGGAGTAA 2199 CALML4 0.31 TTGGACATCTCTAGTGTAGCTGCCA

TABLE 77 Floxuridine biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 2200 CSDA 0.33 ACTTGTCCTCAGCTTGGGCTTCTTC 2201 F8A1 0.31TGGACCCCACTGGCTGAGAATCTGG 2202 KYNU 0.32 TGGACCCCACTGGCTGAGAATCTGG 2203PHF14 0.31 AAGCCTATACGTTTCTGTGGAGTAA 2204 SERPINB2 0.34TCCTCCATCACCTGAAACACTGGAC 2205 OPHN1 0.31 GCCCCACTGGACAACACTGATTCCT 2206HRMT1L2 0.31 AAGCCTATACGTTTCTGTGGAGTAA 2207 TNFRSF1A 0.3GCCCCACTGGACAACACTGATTCCT 2208 PPP4C 0.31 AAGCCTATACGTTTCTGTGGAGTAA 2209CES1 0.3 TCCTCCATCACCTGAAACACTGGAC 2210 TP53AP1 0.3GCCCCACTGGACAACACTGATTCCT 2211 TM4SF4 0.32 GCCCCACTGGACAACACTGATTCCT2212 RPL5 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 2213 BC008967 0.32TGGACCCCACTGGCTGAGAATCTGG 2214 TLK2 0.35 TTGGACATCTCTAGTGTAGCTGCCA 2215COL4A6 0.31 TCCTTGTGCCTGCTCCTGTACTTGT 2216 PAK3 0.32CACCCAGCTGGTCCTGTGGATGGGA 2217 RECK 0.34 TCCTTGTGCCTGCTCCTGTACTTGT 2218LOC51321 0.32 AAGCCTATACGTTTCTGTGGAGTAA 2219 MST4 0.36TCCTCCATCACCTGAAACACTGGAC 2220 DERP6 0.32 TGGACCCCACTGGCTGAGAATCTGG 2221SCD4 0.33 TCCTTGTGCCTGCTCCTGTACTTGT 2222 FLJ22800 0.31TGGACCCCACTGGCTGAGAATCTGG

TABLE 78 Irinotecan biomarkers. SEQ ID Corre- NO Gene lation Medianprobe2223 CSDA 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 2224 UBE2L6 0.32GCCCCACTGGACAACACTGATTCCT 2225 TAP1 0.44 TGGACCCCACTGGCTGAGAATCTGG 2226RPS19 0.32 TGCCTGCTCCTGTACTTGTCCTCAG 2227 SERPINA1 0.32ACTTGTCCTCAGCTTGGGCTTCTTC 2228 C1QR1 0.31 TTGGACATCTCTAGTGTAGCTGCCA 2229SLA 0.33 CACCCAGCTGGTCCTGTGGATGGGA 2230 GPSM3 0.46TGCCTGCTCCTGTACTTGTCCTCAG 2231 PSMB9 0.3 TGCCTGCTCCTGTACTTGTCCTCAG 2232EDG1 0.34 TGCCTGCTCCTGTACTTGTCCTCAG 2233 FMNL1 0.4GCCCCACTGGACAACACTGATTCCT 2234 PTPN7 0.39 TTGGACATCTCTAGTGTAGCTGCCA 2235ZNFN1A1 0.32 AAGCCTATACGTTTCTGTGGAGTAA 2236 CENTB1 0.33TTGGACATCTCTAGTGTAGCTGCCA 2237 BATF 0.41 ACTTGTCCTCAGCTTGGGCTTCTTC 2238MAP4K1 0.39 AAATGTTTCCTTGTGCCTGCTCCTG 2239 PDE4C 0.31AAGCCTATACGTTTCTGTGGAGTAA 2240 SP110 0.35 TCCTTGTGCCTGCTCCTGTACTTGT 2241HLA-DRA 0.31 TGGACCCCACTGGCTGAGAATCTGG 2242 IFI16 0.36TTGGACATCTCTAGTGTAGCTGCCA 2243 HLA-DRB1 0.32 AAGCCTATACGTTTCTGTGGAGTAA2244 ARHGEF6 0.43 ACTTGTCCTCAGCTTGGGCTTCTTC 2245 SELPLG 0.35TCCTTGTGCCTGCTCCTGTACTTGT 2246 SEC31L2 0.35 CACCCAGCTGGTCCTGTGGATGGGA2247 CD3Z 0.51 TCCTCCATCACCTGAAACACTGGAC 2248 PRKCQ 0.39TTGGACATCTCTAGTGTAGCTGCCA 2249 SH2D1A 0.43 AAGCCTATACGTTTCTGTGGAGTAA2250 GZMB 0.49 TCCTCCATCACCTGAAACACTGGAC 2251 TRB@ 0.43ACTTGTCCTCAGCTTGGGCTTCTTC 2252 HLA-DPA1 0.47 ACTTGTCCTCAGCTTGGGCTTCTTC2253 AIM1 0.36 TCCTTGTGCCTGCTCCTGTACTTGT 2254 DOCK2 0.39TGGACCCCACTGGCTGAGAATCTGG 2255 CD3D 0.31 TCCTGTACTTGTCCTCAGCTTGGGC 2256IFITM1 0.31 TTGGACATCTCTAGTGTAGCTGCCA 2257 ZAP70 0.31GCCCCACTGGACAACACTGATTCCT 2258 PRF1 0.47 CACCCAGCTGGTCCTGTGGATGGGA 2259Clorf24 0.39 GCCCCACTGGACAACACTGATTCCT 2260 ARHGAP15 0.48TCCTCCATCACCTGAAACACTGGAC 2261 C13orf18 0.33 CACCCAGCTGGTCCTGTGGATGGGA2262 TM6SF1 0.37 TCCTTGTGCCTGCTCCTGTACTTGT

TABLE 79 Satraplatin biomarkers. SEQ ID Corre- NO Gene lationMedianprobe 2263 STAT1 0.32 TCCTGTACTTGTCCTCAGCTTGGGC 2264 HSBP1 0.33AAATGTTTCCTTGTGCCTGCTCCTG 2265 IFI30 0.35 AAGCCTATACGTTTCTGTGGAGTAA 2266RIOK3 0.36 TCCTCCATCACCTGAAACACTGGAC 2267 TNFSF10 0.31ACTTGTCCTCAGCTTGGGCTTCTTC 2268 ALOX5AP 0.3 TCCTTGTGCCTGCTCCTGTACTTGT2269 ADFP 0.33 TGGACCCCACTGGCTGAGAATCTGG 2270 IRS2 0.37TCCTGTACTTGTCCTCAGCTTGGGC 2271 EFEMP2 0.31 TTGGACATCTCTAGTGTAGCTGCCA2272 RTPK2 0.35 TGGACCCCACTGGCTGAGAATCTGG 2273 DKFZp564I1922 0.33TCCTCCATCACCTGAAACACTGGAC 2274 MT1K 0.34 TCCTCCATCACCTGAAACACTGGAC 2275RNASET2 0.38 ACTTGTCCTCAGCTTGGGCTTCTTC 2276 EFHD2 0.31CACCCAGCTGGTCCTGTGGATGGGA 2277 TRIB3 0.33 GCCCCACTGGACAACACTGATTCCT 2278ACSL5 0.42 AAATGTTTCCTTGTGCCTGCTCCTG 2279 IFIH1 0.37ACTTGTCCTCAGCTTGGGCTTCTTC 2280 DNAPTP6 0.42 TGCCTGCTCCTGTACTTGTCCTCAG

TABLE 80 Vincristine microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2281 Hcd892 left 0.3 GAGGGCTGGAGAGGTTGGGTGCGCTTGTGCGTTTCACTTT2282 Hcd678 right 0.27 GCCCTGAAGCTCCGGACTACAGCTCCCAGGCCTCTCCAAG 2283mir-007-1-prec 0.28 TGTTGGCCTAGTTCTGTGTGGAAGACTAGTGATTTTGTTG 2284 MPR243left 0.25 GTATTTACCTAGTTGTAATGTGGGTTGCCATGGTGTTTTG 2285 Hcd654 left 0.25AACGAGTAAAAGGCGTACATGGGAGCGCGGGGCGGCAGAG 2286 mir-487No1 0.26TTATGACGAATCATACAGGGACATCCAGTTTTTCAGTATC 2287 Hcd794 right 0.35GGCCACCACAGACACCAACAAGTTCAGTCCGTTTCTGCAG 2288 Hcd739 right 0.32TATTAGCTGAGGGAGGGCTGGAGGCGGCTGCATTCCGACT 2289 Hcd562 right 0.28CGCATGTCCTGGCCCTCGTCCTTCCATGGCACTGGCACCG

TABLE 81 Cisplatin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2290 HUMTRF 0.34 GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 2291HPR187 right 0.25 TATTTATTACAAGGTCCTTCTTCCCCGTAAAACTTTGTCC 2292mir-450-1 0.26 AACGATACTAAACTGTTTTTGCGATGTGTTCCTAATATGC 2293mir-155-prec 0.31 TTAATGCTAATCGTGATAGGGGTTTTTGCCTCCAACTGAC 2294mir-515-15p 0.25 GATCTCATGCAGTCATTCTCCAAAAGAAAGCACTTTCTGT 2295mir-181b-precNo2 0.25 ACCATCGACCGTTGATTGTACCCTATGGCTAACCATCATC 2296mir-124a-1-prec1 0.26 ATACAATTAAGGCACGCGGTGAATGCCAAGAATGGGGCTG 2297mir-450-2No1 0.3 GAAAGATGCTAAACTATTTTTGCGATGTGTTCCTAATATG 2298 Hcd923right 0.31 CTGGAGATAATGATTCTGCATTTCTAATTAACTCCCAGGT 2299 mir-342No1 0.31GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 2300 mir-142-prec 0.27CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2301 mir-223-prec 0.26GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 2302 Hcd754 left 0.38TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC 2303 Hcd213_HPR182 left 0.3CTGTTTCATACTTGAGGAGAAATTATCCTTGGTGTGTTCG

TABLE 82 Azaguanine microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2304 MPR121 left 0.3 CACCTGGCTCTGAGAACTGAATTCCATAGGCTGTGAGCTC2305 HUMTRS 0.26 TCTAGCGACAGAGTGGTTCAATTCCACCTTTCGGGCGCCA 2306mir-213-precNo1 0.26 AACATTCATTGCTGTCGGTGGGTTGAACTGTGTGGACAAG 2307mir-155-prec 0.4 TTAATGCTAATCGTGATAGGGGTTTTTGCCTCCAACTGAC 2308mir-147-prec 0.47 GACTATGGAAGCCAGTGTGTGGAAATGCTTCTGCTAGATT 2309mir-100No1 0.26 CCTGTTGCCACAAACCCGTAGATCCGAACTTGTGGTATTA 2310mir-138-1-prec 0.29 AGCTGGTGTTGTGAATCAGGCCGTTGCCAATCAGAGAACG 2311mir-140No2 0.38 TTCTACCACAGGGTAGAACCACGGACAGGATACCGGGGCA 2312mir-146-prec 0.51 TGAGAACTGAATTCCATGGGTTGTGTCAGTGTCAGACCTC 2313mir-509No1 0.25 ATTAAAAATGATTGGTACGTCTGTGGGTAGAGTACTGCAT 2314mir-146bNo1 0.33 CACCTGGCACTGAGAACTGAATTCCATAGGCTGTGAGCTC 2315 Hcd514right 0.26 ATTAGAGACTCGTTAAGAGAAGGTGAGAAGGGCTCAGTAA 2316 Hcd397 left0.34 GTGTGTATACTTATGTGTGTGTATGTGTGAGTGTGAATAT 2317 Hcd731 left 0.27AATTGTGACAACTGAGTGGGAGGTTTGTGTGATGATTATC 2318 mir-034-precNo2 0.32AGTAAGGAAGCAATCAGCAAGTATACTGCCCTAGAAGTGC 2319 mir-100-1/2-prec 0.3TGAGGCCTGTTGCCACAAACCCGTAGATCCGAACTTGTGG

TABLE 83 Etoposide microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2320 Hcd415 right 0.28 GATGTTTGGGAAACAATGGGAGTGAGAGAATGGGAGAGCT2321 Hcd768 right 0.37 GCCCTGGCGGAACGCTGAGAAGACAGTCGAACTTGACTAT 2322HUMTRF 0.38 GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 2323 Hcd866 right0.26 GTCATGCTGCCACCAGCAGGCAGAGAAGAAGCAGAAGAAC 2324 Hcd145 left 0.33AAAAATCCCAGCGGCCACCTTTCCTCCCTGCCCCATTGGG 2325 HUMTRAB 0.29ATGGTAGAGCGCTCGCTTTGCTTGCGAGAGGTAGCGGGAT 2326 Hcd913 right 0.36CAAACATCATGTGACGTCTGTGGAGCGGCGGCGGCGGCGG 2327 HPR163 left 0.29GCTGCCCCCTCCCTTAGCAACGTGGCCCCGGCGTTCCAAA 2328 Hcd697 right 0.27GGCCTCATGCTGCCAAGGGCTGGCAAGAAGTCCCTGCTTG 2329 Hcd755 left 0.26GGAAGTGGAGCAAATGGATGGAAAGCAATTTTTGGAAGAT 2330 Hcd716 right 0.25CAATAAATGTGCCTATAAAGGCGCCGGCTCCGGGGCGCGG 2331 MPR207 right 0.33AACAACTTTGTGCTGGTGCCGGGGAAGTTTGTGTCTCCTA 2332 HSTRNL 0.26TCCGGATGGAGCGTGGGTTCGAATCCCACTTCTGACACCA 2333 HPR206 left 0.29CTATATTGGACCGCAGCGCTGAGAGCTTTTGTGTTTAATG 2334 MPR243 left 0.27GTATTTACCTAGTTGTAATGTGGGTTGCCATGGTGTTTTG 2335 Hcd654 left 0.4AACGAGTAAAAGGCGTACATGGGAGCGCGGGGCGGCAGAG 2336 MPR130 left 0.28AGGCCAAGGTGACGGGTGCGATTTCTGTGTGAGACAATTC 2337 Hcd782 left 0.26GGAGCCCTGTCTGCAAAGAGTGGTGCGTGTGCGTGTGTGA 2338 Hcd794 right 0.26GGCCACCACAGACACCAACAAGTTCAGTCCGTTTCTGCAG 2339 Hcd739 right 0.3TATTAGCTGAGGGAGGGCTGGAGGCGGCTGCATTCCGACT 2340 mir-142-prec 0.29CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2341 HSHELA01 0.29GGCCGCAGCAACCTCGGTTCGTATCCGAGTCACGGCACCA 2342 HUMTRV1A 0.29ACGCGAAAGGTCCCCGGTTCGAAACCGGGCGGAAACACCA 2343 Hcd754 left 0.34TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC

TABLE 84 Carboplatin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2344 Hcd829 right 0.27 AAAATGGCGGCGGGAAAAGCGAGCGGCGAGAGCGAGGAGG2345 HUMTRF 0.26 GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 2346 HPR187left 0.29 TGTGTGTTGCGGGGGTGGGGGCCGGTGAAAGTGATTTGAT 2347 Hcd210_HPR205right 0.32 CGAAACATTCGCGGTGCACTTCTTTTTCAGTATCCTATTC 2348 mir-379No1 0.26TTCCGTGGTTCCTGAAGAGATGGTAGACTATGGAACGTAG 2349 mir-213-precNo1 0.26AACATTCATTGCTGTCGGTGGGTTGAACTGTGTGGACAAG 2350 mir-4325p 0.29CCAGGTCTTGGAGTAGGTCATTGGGTGGATCCTCTATTTC 2351 mir-450-1 0.3AACGATACTAAACTGTTTTTGCGATGTGTTCCTAATATGC 2352 mir-155-prec 0.25TTAATGCTAATCGTGATAGGGGTTTTTGCCTCCAACTGAC 2353 Hcd28_HPR39right 0.26AAGCTCCCAAATTAGCTTTTTAAATAGAAGCTGAGAGTTA 2354 MPR244 right 0.27TAAACATAGAGGAAATTTCACGTTTTCAGTGTCAAATGCT 2355 mir-409-3p 0.3GACGAATGTTGCTCGGTGAACCCCTTTTCGGTATCAAATT 2356 mir-124a-1-prec1 0.28ATACAATTAAGGCACGCGGTGAATGCCAAGAATGGGGCTG 2357 mir-154-prec1No1 0.26GTGGTACTTGAAGATAGGTTATCCGTGTTGCCTTCGCTTT 2358 mir-495No1 0.32GTGACGAAACAAACATGGTGCACTTCTTTTTCGGTATCAA 2359 mir-515-23p 0.25CAGAGTGCCTTCTTTTGGAGCGTTACTGTTTGAGAAAAAC 2360 Hcd438 right 0.27GTGTTTATTTGAATCTCACATCGCTCATAAGAATACACGC 2361 Hcd770 left 0.3CCAGTATACAATCCGTTTTTCAGTTTAGCTTGAGATCAGA 2362 mir-382 0.32GGTACTTGAAGAGAAGTTGTTCGTGGTGGATTCGCTTTAC 2363 mir-223-prec 0.3GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 2364 Hcd754 left 0.48TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC 2365 Hcd213_HPR182 left 0.31CTGTTTCATACTTGAGGAGAAATTATCCTTGGTGTGTTCG

TABLE 85 Adriamycin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2366 Hcd768 right 0.25 GCCCTGGCGGAACGCTGAGAAGACAGTCGAACTTGACTAT2367 mir-483No1 0.28 ATCACGCCTCCTCACTCCTCTCCTCCCGTCTTCTCCTCTC 2368Hcd145 left 0.28 AAAAATCCCAGCGGCCACCTTTCCTCCCTGCCCCATTGGG 2369mir-197-prec 0.25 TAAGAGCTCTTCACCCTTCACCACCTTCTCCACCCAGCAT 2370mir-212-precNo1 0.27 CCTCAGTAACAGTCTCCAGTCACGGCCACCGACGCCTGGC 2371HPR163 left 0.3 GCTGCCCCCTCCCTTAGCAACGTGGCCCCGGCGTTCCAAA 2372 Hcd654left 0.26 AACGAGTAAAAGGCGTACATGGGAGCGCGGGGCGGCAGAG 2373 mir-342No1 0.32GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 2374 Hcd794 right 0.32GGCCACCACAGACACCAACAAGTTCAGTCCGTTTCTGCAG 2375 mir-142-prec 0.38CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2376 Hcd754 left 0.28TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC

TABLE 86 Aclarubicin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2377 mir-092-prec-X = 092-2 0.32GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG 2378 mir-096-prec-7No2 0.29TGGCCGATTTTGGCACTAGCACATTTTTGCTTGTGTCTCT 2379 Hcd605 left 0.26ATTACTAGCAGTTAATGATTGGTTTGTTAGTTAATGGCCC 2380 mir-007-2-precNo2 0.34GGACCGGCTGGCCCCATCTGGAAGACTAGTGATTTTGTTG 2381 mir-019b-2-prec 0.28GTGGCTGTGCAAATCCATGCAAAACTGATTGTGATAATGT 2382 MPR216 left 0.26GATCCTAGTAGTGCCAAAGTGCTCATAGTGCAGGTAGTTT 2383 mir-019b-1-prec 0.25TTCTGCTGTGCAAATCCATGCAAAACTGACTGTGGTAGTG 2384 mir-135-2-prec 0.26CACTCTAGTGCTTTATGGCTTTTTATTCCTATGTGATAGT 2385 HSTRNL 0.26TCCGGATGGAGCGTGGGTTCGAATCCCACTTCTGACACCA 2386 mir-025-prec 0.31ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 2387 mir-007-1-prec 0.4TGTTGGCCTAGTTCTGTGTGGAAGACTAGTGATTTTGTTG 2388 mir-019a-prec 0.26TGTAGTTGTGCAAATCTATGCAAAACTGATGGTGGCCTGC 2389 mir-380-5p 0.31AGGTACCTGAAAAGATGGTTGACCATAGAACATGCGCTAT 2390 mir-093-prec-7.1 = 093-10.37 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 2391 mir-106-prec-X 0.37CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2392 mir-142-prec 0.32CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2393 mir-018-prec 0.31TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC 2394 mir-020-prec 0.36TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 87 Mitoxantrone microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2395 Hcd768 left 0.26 GATGGTTTAGTGAGGCCCTCGGATCAGCCCGCTGGGTCAG2396 HUMTRF 0.31 GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 2397mir-213-precNo1 0.28 AACATTCATTGCTGTCGGTGGGTTGAACTGTGTGGACAAG 2398mir-181b-precNo1 0.26 TGAGGTTGCTTCAGTGAACATTCAACGCTGTCGGTGAGTT 2399M2R244 right 0.27 TAAACATAGAGGAAATTTCACGTTTTCAGTGTCAAATGCT 2400mir-409-3p 0.29 GACGAATGTTGCTCGGTGAACCCCTTTTCGGTATCAAATT 2401 HSTRNL0.33 TCCGGATGGAGCGTGGGTTCGAATCCCACTTCTGACACCA 2402 mir-382 0.34GGTACTTGAAGAGAAGTTGTTCGTGGTGGATTCGCTTTAC 2403 mir-342No1 0.3GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 2404 mir-142-prec 0.27CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2405 Hcd200 right 0.29CAATTAGCCAATTGTGGGTATAATTAGCTGCATGTAGAAT

TABLE 88 Mitomycin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2406 HUMTRF 0.26 GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 2407Hcd148_HPR225left 0.27 AATTAATGACCAAAATGTCAGATGTGTCCACAGCTAATTA 2408Hcd938 right 0.26 ATTCCCTGCATCACTCTCATGAAATGGCTGAGAAAGTGAG 2409 MPR174left 0.32 GAGCCGGTCTCTTTACATCTCAAATACCAGGTATTTAGGT 2410 mir-4323p 0.29CCTTACGTGGGCCACTGGATGGCTCCTCCATGTCTTGGAG

TABLE 89 Paclitaxel (Taxol) microRNA biomarkers. SEQ ID NO MedianprobeCorr Sequence 2411 mir-092-prec-X = 092-2 0.29GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG 2412 mir-096-prec-7No1 0.36CTCCGCTCTGAGCAATCATGTGCAGTGCCAATATGGGAAA 2413 mir-101-prec-9 0.38GCTGTATATCTGAAAGGTACAGTACTGTGATAACTGAAGA 2414 mir-20bNo1 0.28AGTACCAAAGTGCTCATAGTGCAGGTAGTTTTGGCATGAC 2415 mir-019b-2-prec 0.28GTGGCTGTGCAAATCCATGCAAAACTGATTGTGATAATGT 2416 mir-032-precNo2 0.29GGAGATATTGCACATTACTAAGTTGCATGTTGTCACGGCC 2417 MPR156 left 0.25TCCCTCACTTGAACTGACTGCCAGAGTTCACAGACAGCTG 2418 mir-019b-1-prec 0.28TTCTGCTGTGCAAATCCATGCAAAACTGACTGTGGTAGTG 2419 mir-135-2-prec 0.36CACTCTAGTGCTTTATGGCTTTTTATTCCTATGTGATAGT 2420 mir-025-prec 0.36ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 2421 mir-007-1-prec 0.27TGTTGGCCTAGTTCTGTGTGGAAGACTAGTGATTTTGTTG 2422 mir-361No1 0.29GGATTTGGGAGCTTATCAGAATCTCCAGGGGTACTTTATA 2423 mir-093-prec-7.1 = 093-10.37 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 2424 mir-106-prec-X 0.38CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2425 mir-098-prec-X 0.29TGAGGTAGTAAGTTGTATTGTTGTGGGGTAGGGATATTAG 2426 mir-142-prec 0.27CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2427 HPR169 right 0.26GTTTCTTTCTCACGGTAACTGGCAGCCTCGTTGTGGGCTG 2428 mir-018-prec 0.4TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC 2429 mir-020-prec 0.36TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 90 Gemcitabine (Gemzar) microRNA biomarkers. SEQ ID NO MedianprobeCorr Sequence 2430 mir-123-precNo2 0.27TGTGACACTTCAAACTCGTACCGTGAGTAATAATGCGCCG 2431 Hcd257 right 0.29CTTGGTTTTTGCAATAATGCTAGCAGAGTACACACAAGAA 2432 mir-155-prec 0.35TTAATGCTAATCGTGATAGGGGTTTTTGCCTCCAACTGAC 2433 ath-MIR180aNo2 0.26TGAGAATCTTGATGATGCTGCATCGGCAATCAACGACTAT 2434 Hcd448 left 0.33TGTAATTCCATTGAGGGTTTCTGGTGACTCCAGCTTCGTA 2435 HSTRNL 0.31TCCGGATGGAGCGTGGGTTCGAATCCCACTTCTGACACCA 2436 MPR174 right 0.29CATTAGGGACACGTGTGAGTGTGCCAGGCTCATTCCTGAG 2437 Hcd200 right 0.29CAATTAGCCAATTGTGGGTATAATTAGCTGCATGTAGAAT 2438 mir-4323p 0.26CCTTACGTGGGCCACTGGATGGCTCCTCCATGTCTTGGAG 2439 HPR244 right 0.3TAGTTCATGGCGTCCAGCAGCAGCTTCTGGCAGACCGGGT

TABLE 91 Taxotere (docetaxel) microRNA biomarkers. SEQ ID NO MedianprobeCorr Sequence 2440 mir-096-prec-7No1 0.28CTCCGCTCTGAGCAATCATGTGCAGTGCCAATATGGGAAA 2441 mir-095-prec-4 0.27CGTTACATTCAACGGGTATTTATTGAGCACCCACTCTGTG 2442 HSTRNL 0.26TCCGGATGGAGCGTGGGTTCGAATCCCACTTCTGACACCA 2443 mir-007-1-prec 0.37TGTTGGCCTAGTTCTGTGTGGAAGACTAGTGATTTTGTTG

TABLE 392 Dexamethasone microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2444 MPR141 left 0.42 CTCAGTCGTGCCCTAGCAGCGGGAACAGTACTGCAGTGAG2445 mir-424No2 0.35 GTTCAAAACGTGAGGCGCTGCTATACCCCCTCGTGGGGAA 2446Hcd690 right 0.26 GGACAAGGGAGGAGACACGCAGAGGTGACAGAAAGGTTAG 2447 Hcd783left 0.26 CAGGCTCACACCTCCCTCCCCCAACTCTCTGGAATGTATA 2448 mir-150-prec0.38 CTCCCCATGGCCCTGTCTCCCAACCCTTGTACCAGTGCTG 2449 Hcd266 left 0.37AAGGTCTTTGGTCTTGGAGGAAGGTGTGCTACTGGAAGAG 2450 mir-503No1 0.34CTCAGCCGTGCCCTAGCAGCGGGAACAGTTCTGCAGTGAG 2451 mir-128b-precNo1 0.29TCACAGTGAACCGGTCTCTTTCCCTACTGTGTCACACTCC 2452 Hcd397 left 0.26GTGTGTATACTTATGTGTGTGTATGTGTGAGTGTGAATAT 2453 mir-484 0.38GTCAGGCTCAGTCCCCTCCCGATAAACCCCTAAATAGGGA

TABLE 93 Ara-C (Cytarabine hydrochloride) microRNA biomarkers. SEQ ID NOMedianprobe Corr Sequence 2454 HUMTRF 0.33GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 2455 mir-155-prec 0.28TTAATGCTAATCGTGATAGGGGTTTTTGCCTCCAACTGAC 2456 mir-515-15p 0.27GATCTCATGCAGTCATTCTCCAAAAGAAAGCACTTTCTGT 2457 Hcd938 right 0.26ATTCCCTGCATCACTCTCATGAAATGGCTGAGAAAGTGAG 2458 Hcd642 right 0.25TCAGGGTTTATGAAGTTATCAAAGCCCCTTGATGGAATTA 2459 Hcd120 left 0.26CTTGGTGTGTTCTCGGTAGCTATGGAAATCCCAGGGTTTC 2460 mir-380-5p 0.25AGGTACCTGAAAAGATGGTTGACCATAGAACATGCGCTAT 2461 mir-342No1 0.25GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 2462 mir-142-prec 0.27CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2463 mir-223-prec 0.31GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 2464 mir-4323p 0.28CCTTACGTGGGCCACTGGATGGCTCCTCCATGTCTTGGAG

TABLE 94 Methylprednisolone microRNA biomarkers. SEQ ID NO MedianprobeCorr Sequence 2465 Hcd544 left 0.26TTCCAGGTGTCCACCAAGGACGTGCCGCTGGCGCTGATGG 2466 mir-181c-precNo1 0.28TGCCAAGGGTTTGGGGGAACATTCAACCTGTCGGTGAGTT 2467 Hcd517 left 0.25TTAAAGCAGGAGAGGTGAGAGGAAGAATTAATGTGTGCTC 2468 MPR151 left 0.27GGGATTAATGACCAGCTGGGGGAGTTGATAGCCCTCAGTG 2469 mir-213-precNo1 0.34AACATTCATTGCTGTCGGTGGGTTGAACTGTGTGGACAAG 2470 mir-181b-precNo2 0.36ACCATCGACCGTTGATTGTACCCTATGGCTAACCATCATC 2471 mir-150-prec 0.27CTCCCCATGGCCCTGTCTCCCAACCCTTGTACCAGTGCTG 2472 mir-153-1-prec1 0.28CAGTTGCATAGTCACAAAAGTGATCATTGGCAGGTGTGGC 2473 mir-128b-precNo1 0.48TCACAGTGAACCGGTCTCTTTCCCTACTGTGTCACACTCC 2474 Hcd812 left 0.25CTGTGGGATCTGGTTCTGTAGCTGAGAGCACATCGCTAAA 2475 mir-195-prec 0.3TCTAGCAGCACAGAAATATTGGCACAGGGAAGCGAGTCTG 2476 mir-342No1 0.38GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 2477 mir-370No1 0.28TTACACAGCTCACGAGTGCCTGCTGGGGTGGAACCTGGTC 2478 mir-142-prec 0.32CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2479 mir-223-prec 0.36GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 2480 mir-484 0.36GTCAGGCTCAGTCCCCTCCCGATAAACCCCTAAATAGGGA

TABLE 95 Methotrexate microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2481 mir-092-prec-X = 092-2 0.37GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG 2482 mir-096-prec-7No1 0.33CTCCGCTCTGAGCAATCATGTGCAGTGCCAATATGGGAAA 2483 mir-123-precNo1 0.25GACGGGACATTATTACTTTTGGTACGCGCTGTGACACTTC 2484 Hcd250 left 0.26GTTCTGTTGCTAAGACAACAGGATGCTAGCAGGCATATGC 2485 mir-518e/526c 0.3TCTCAGGCTGTGACCCTCTAGAGGGAAGCGCTTTCTGTTG 2486 HPR232 right 0.3TGAATTATTGCACAATAAATTCATGCCCTCTTGTGTCTTA 2487 Hcd263 left 0.29GAGCATTAAGATTTCCTATTCTTTGAGGCAAATATTGACC 2488 mir-516-33p 0.35GTGAAAGAAAGTGCTTCCTTTCAGAGGGTTACTCTTTGAG 2489 Hcd605 left 0.27ATTACTAGCAGTTAATGATTGGTTTGTTAGTTAATGGCCC 2490 Hcd373 right 0.25CCTGAAAGGTCTGGTGTTAAGCAAATACTCGGTGACCAGA 2491 MPR254 right 0.28GTTCACAGTGGGAGAAATATGCTTCGTATTACTCTTTCTC 2492 MPR215 left 0.3CAGCTATGTGGACTCTAGCTGCCAAAGGCGCTTCTCCTTC 2493 HUMTRF 0.28GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 2494 mir-106aNo1 0.27CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2495 mir-20bNo1 0.37AGTACCAAAGTGCTCATAGTGCAGGTAGTTTTGGCATGAC 2496 Hcd361 right 0.28AACTTGGCTACAAGGCTCTTTCCCTCTCTATGAAGGACAG 2497 Hcd412 left 0.25AGTTGGGGAGAACTTTATGATTATTCTCATGCATCATCTT 2498 Hcd781 left 0.26GAGTGTGGATCTAATCTTCAGCTGATTAAATGTCCCTCAT 2499 mir-019b-2-prec 0.33GTGGCTGTGCAAATCCATGCAAAACTGATTGTGATAATGT 2500 HPR214 right 0.29AGCAAAAGCTATTATTTGCCCTTGATGAGCCAATCAGATG 2501 Hcd807 right 0.26GCGCTGACAAATCTTGCCTGATTCTGTATGATCCATGAGA 2502 Hcd817 left 0.37TAATGAGAATTATGTTTGCACATTGAGGCAGGATAAATCC 2503 Hcd788 left 0.25GACAAACATGCAGGAAAAATTATCCCCTGGGGATTCTACA 2504 Hcd970 left 0.31TTGTGGGTCAGCTGCCCAGCTATCGGCTGGATTAGTGAAT 2505 Hcd148_HPR225left 0.26AATTAATGACCAAAATGTCAGATGTGTCCACAGCTAATTA 2506 Hcd102 left 0.27ACTGGAATTATGTTTTATCTTAAGTCCACACTGGATCCTC 2507 Hcd246 right 0.29TAAAGTGAGTTATGGAGGTTACTCTCCTGTGAGAGGAAAT 2508 HPR199 right 0.28TACACCTAAGGCATGTACTGTATTAATGAACCAATAAAAC 2509 HPR233 right 0.27CATGATGGGGTGGGGTGAGATGGGGAGCGAAGACTATTAC 2510 Hcd383 left 0.28GCCCGGGCATGCATTTTATCTAGCACCATGTGTTTCAGCT 2511 MPR224 right 0.29TGAATTATTGCACAATAAATTCATGCCCTGTTGTGTCTTA 2512 HPR172 right 0.26GTTTAAACAGCCAGTGCAAACATTTAGATCTGAGTCAAAA 2513 MPR216 left 0.34GATCCTAGTAGTGCCAAAGTGCTCATAGTGCAGGTAGTTT 2514 mir-321No2 0.25CAGGGATTGTGGGTTCGAGTCCCACCCGGGGTAAAGAAAG 2515 Hcd586 right 0.28GAACTGTTTGCTTTGGATGGGCTTGGTCCTCATTGGCTGA 2516 Hcd587 right 0.3AAATAATGACTGGCCATAAGATCAAGACAAGTGTCCAAAG 2517 Hcd249 right 0.39CAGGTACATGTTGATCAGCAGGGGCTGGGAGGCGCCGCTC 2518 Hcd279 right 0.27CTCACGGCGTTGCCATGGAGACAACTCCGGGGCTGGGGCTC 2519 HPR159 left 0.3TCCGTCACTTGAACTGGCTGCCAGCGTTCACAGACAGCTG 2520 Hcd689 right 0.28GTACATCTGGATGTAGTTGTGCTGCAGCTGCTTCTGGTAG 2521 Hcd691 right 0.32CGGCAAAAACCTCTGTCAGAACAAAATTAGGTGATCTATC 2522 mir-019b-1-prec 0.32TTCTGCTGTGCAAATCCATGCAAAACTGACTGTGGTAGTG 2523 Hcd413 right 0.26CACAAAAAGGCATAAGCAGACATCTTGCCCTTTGGTTTCT 2524 Hcd581 right 0.26AGGAGATATGCCAAGATATATTCACAGCTTTATATACACA 2525 Hcd536_HPR104 right 0.28GCTGCTCTGCTGAGGGGCTGGACTCTGTCCAGAAGCACCA 2526 Hcd230 left 0.28CATTCTCTACAAGCATATGGCCTTGGGACATTAAGATGGC 2527 HPR154 left 0.28AACATCAAGATCTATTGACCTGAGAGGTAAATATTGACCG 2528 Hcd270 right 0.31AAATGTTGTTATAGTATCCCACCTACCCTGATGTATCTTT 2529 Hcd649 right 0.26GAACAGGCTTCAAGGTTCTTGGCAGGAATATTCCGTGTAG 2530 Hcd889 right 0.27ATGCCTTGTGCTCTGTGCTAATTCAGAAGAATAAGCCTGT 2531 Hcd938 left 0.36CTTGTCGACTAGCCAGTTATGAACAGAGGAGGATGTTCTC 2532 HPR266 right 0.32GGAGATCCCTTCAAGGTACTTAGTTTTAAATGAGTGCTCT 2533 mir-025-prec 0.39ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 2534 Hcd355_HPR190 left 0.25TTGTGCACTGCACAACCCTAGTGGCGCCATTCAATTATAG 2535 MPR162 left 0.26CTCTCTTTTTCCTGCTTGATTTGCCTAATGGAAGCTGACA 2536 Hcd923 right 0.34CTGGAGATAATGATTCTGCATTTCTAATTAACTCCCAGGT 2537 MPR237 left 0.32AGCACATCCCATGATCACAGTAATGTTCTTTGGAGATGTA 2538 MPR174 left 0.32GAGCCGGTCTCTTTACATCTCAAATACCAGGTATTTAGGT 2539 mir-019a-prec 0.31TGTAGTTGTGCAAATCTATGCAAAACTGATGGTGGCCTGC 2540 hsa_mir_490_Hcd20 right0.25 ACCAACCTGGAGGACTCCATGCTGTTGAGCTGTTCACAAG 2541 mir-380-5p 0.36AGGTACCTGAAAAGATGGTTGACCATAGAACATGCGCTAT 2542 mir-093-prec-7.1 = 093-10.38 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 2543 mir-106-prec-X 0.45CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2544 Hcd627 left 0.3GCATTAGGGAGAATAGTTGATGGATTACAAATCTCTGCAT 2545 mir-142-prec 0.27CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2546 HPR169 right 0.29GTTTCTTTCTCACGGTAACTGGCAGCCTCGTTGTGGGCTG 2547 mir-001b-2-prec 0.28TAAGCTATGGAATGTAAAGAAGTATGTATCTCAGGCCGGG 2548 mir-018-prec 0.4TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC 2549 mir-020-prec 0.48TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG 2550 Hcd404 left 0.29TGCTGCTGTTAATGCCATTAGGATGACTATTTATATCACC 2551 mir-384 0.25CATAAGTCATTCCTAGAAATTGTTCATAATGCCTGTAACA 2552 mir-4323p 0.4CCTTACGTGGGCCACTGGATGGCTCCTCCATGTCTTGGAG

TABLE 96 Bleomycin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2553 mir-376aNo1 0.27 AATCATAGAGGAAAATCCACGTTTTCAGTATCAAATGCTG2554 mir-155-prec 0.35 TTAATGCTAATCGTGATAGGGGTTTTTGCCTCCAACTGAC 2555mir-409-3p 0.28 GACGAATGTTGCTCGGTGAACCCCTTTTCGGTATCAAATT 2556 mir-495No10.29 GTGACGAAACAAACATGGTGCACTTCTTTTTCGGTATCAA 2557 Hcd498 right 0.28CACGAAGAAGTTCAGCAACCAGGAGACCAGGTGGGGGCCG 2558 mir-199a-2-prec 0.41TCGCCCCAGTGTTCAGACTACCTGTTCAGGACAATGCCGT 2559 mir-382 0.3GGTACTTGAAGAGAAGTTGTTCGTGGTGGATTCGCTTTAC 2560 HPR271 right 0.27AATTGAGCAAACAGTGCAATTTTCTGTAATTATGCCAGTG 2561 mir-145-prec 0.31CCTCACGGTCCAGTTTTCCCAGGAATCCCTTAGATGCTAA 2562 mir-199a-1-prec 0.35GCCAACCCAGTGTTCAGACTACCTGTTCAGGAGGCTCTCA

TABLE 97 Methyl-GAG (methyl glyoxal bis amidinohydrazonedihydrochloride) microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2563 mir-092-prec-X = 092-2 0.32GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG 2564 mir-101-prec-9 0.3GCTGTATATCTGAAAGGTACAGTACTGTGATAACTGAAGA 2565 mir-144-precNo2 0.29CCCTGGCTGGGATATCATCATATACTGTAAGTTTGCGATG 2566 mir-519a-1/526c 0.29TCAGGCTGTGACACTCTAGAGGGAAGCGCTTTCTGTTGTC 2567 mir-519b 0.33GAAAAGAAAGTGCATCCTTTTAGAGGTTTACTGTTTGAGG 2568 mir-015b-precNo2 0.26TGCTACAGTCAAGATGCGAATCATTATTTGCTGCTCTAGA 2569 mir-106aNo1 0.27CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2570 mir-16-1No1 0.26GTCAGCAGTGCCTTAGCAGCACGTAAATATTGGCGTTAAG 2571 mir-181dNo1 0.27GAGGTCACAATCAACATTCATTGTTGTCGGTGGGTTGTGA 2572 mir-017-precNo2 0.31GTCAGAATAATGTCAAAGTGCTTACAGTGCAGGTAGTGAT 2573 mir-019b-2-prec 0.32GTGGCTGTGCAAATCCATGCAAAACTGATTGTGATAATGT 2574 mir-192No2 0.26TGCCAATTCCATAGGTCACAGGTATGTTCGCCTCAATGCC 2575 mir-213-precNo1 0.25AACATTCATTGCTGTCGGTGGGTTGAACTGTGTGGACAAG 2576 mir-215-precNo2 0.3CATTTCTTTAGGCCAATATTCTGTATGACTGTGCTACTTC 2577 mir-107No1 0.28GGCATGGAGTTCAAGCAGCATTGTACAGGGCTATCAAAGC 2578 mir-200bNo1 0.28GTCTCTAATACTGCCTGGTAATGATGACGGCGGAGCCCTG 2579 mir-103-prec-5 = 103-1 0.3TATGGATCAAGCAGCATTGTACAGGGCTATGAAGGCATTG 2580 mir-519a-1/526c 0.37TCAGGCTGTGACACTCTAGAGGGAAGCGCTTTCTGTTGTC 2581 MPR216 left 0.28GATCCTAGTAGTGCCAAAGTGCTCATAGTGCAGGTAGTTT 2582 mir-019b-1-prec 0.31TTCTGCTGTGCAAATCCATGCAAAACTGACTGTGGTAGTG 2583 mir-107-prec-10 0.29GGCATGGAGTTCAAGCAGCATTGTACAGGGCTATCAAAGC 2584 mir-135-2-prec 0.39CACTCTAGTGCTTTATGGCTTTTTATTCCTATGTGATAGT 2585 mir-103-2-prec 0.29GTAGCATTCAGGTCAAGCAACATTGTACAGGGCTATGAAA 2586 mir-519a-2No2 0.29TCTCAGGCTGTGTCCCTCTACAGGGAAGCGCTTTCTGTTG 2587 mir-025-prec 0.33ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 2588 mir-16-2No1 0.33GTTCCACTCTAGCAGCACGTAAATATTGGCGTAGTGAAAT 2589 MPR95 left 0.28TTGTTGGACACTCTTTCCCTGTTGCACTACTGTGGGCCTC 2590 mir-016b-chr3 0.29GTTCCACTCTAGCAGCACGTAAATATTGGCGTAGTGAAAT 2591 Hcd948 right 0.27TGATATAAATAGTCATCCTAATGGCATTAACAGCAGCACT 2592 mir-195-prec 0.35TCTAGCAGCACAGAAATATTGGCACAGGGAAGCGAGTCTG 2593 mir-093-prec-7.1 = 093 - 10.38 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 2594 mir-106-prec-X 0.42CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2595 mir-142-prec 0.37CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2596 mir-519c/526c 0.27TCTCAGCCTGTGACCCTCTAGAGGGAAGCGCTTTCTGTTG 2597 mir-200a-prec 0.29GTCTCTAATACTGCCTGGTAATGATGACGGCGGAGCCCTG 2598 mir-016a-chr13 0.29CAATGTCAGCAGTGCCTTAGCAGCACGTAAATATTGGCGT 2599 mir-018-prec 0.41TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC 2600 mir-020-prec 0.39TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 98 pXD101 HDAC inhibitors microRNA biomarkers. SEQ ID NOMedianprobe Corr Sequence 2601 mir-092-prec-X = 092-2 0.42GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG 2602 mir-123-precNo2 0.31TGTGACACTTCAAACTCGTACCGTGAGTAATAATGCGCCG 2603 mir-106aNo1 0.36CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2604 mir-20bNo1 0.36AGTACCAAAGTGCTCATAGTGCAGGTAGTTTTGGCATGAC 2605 mir-017-precNo2 0.32GTCAGAATAATGTCAAAGTGCTTACAGTGCAGGTAGTGAT 2606 mir-019b-2-prec 0.42GTGGCTGTGCAAATCCATGCAAAACTGATTGTGATAATGT 2607 mir-033-prec 0.3GTGGTGCATTGTAGTTGCATTGCATGTTCTGGTGGTACCC 2608 mir-092-prec-13 = 092-1No20.31 TCTGTATGGTATTGCACTTGTCCCGGCCTGTTGAGTTTGG 2609 mir-122a-prec 0.29CCTTAGCAGAGCTGTGGAGTGTGACAATGGTGTTTGTGTC 2610 Hcd783 left 0.27CAGGCTCACACCTCCCTCCCCCAACTCTCTGGAATGTATA 2611 MPR216 left 0.29GATCCTAGTAGTGCCAAAGTGCTCATAGTGCAGGTAGTTT 2612 mir-019b-1-prec 0.41TTCTGCTGTGCAAATCCATGCAAAACTGACTGTGGTAGTG 2613 mir-135-2-prec 0.46CACTCTAGTGCTTTATGGCTTTTTATTCCTATGTGATAGT 2614 mir-128b-precNo1 0.39TCACAGTGAACCGGTCTCTTTCCCTACTGTGTCACACTCC 2615 mir-025-prec 0.45ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 2616 Hcd511 right 0.26TACCTCAGAAGCCTCACTCAACCCTCTCCCGCTGAGTCTC 2617 mir-093-prec-7.1 = 093-10.45 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 2618 mir-106-prec-X 0.5CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2619 mir-142-prec 0.5CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2620 HPR169 right 0.26GTTTCTTTCTCACGGTAACTGGCAGCCTCGTTGTGGGCTG 2621 mir-223-prec 0.26GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 2622 mir-018-prec 0.48TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC 2623 mir-020-prec 0.52TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 99 5-Fluorouracil microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2624 mir-096-prec-7No2 0.27TGGCCGATTTTGGCACTAGCACATTTTTGCTTGTGTCTCT 2625 mir-429No1 0.25CTAATACTGTCTGGTAAAACCGTCCATCCGCTGCCTGATC 2626 Hcd693 right 0.25AGGCTTTGTGCGCGCATTAAAGCTCGCCGGACCCCCGACC 2627 HPR214 right 0.27AGCAAAAGCTATTATTTGCCCTTGATGAGCCAATCAGATG 2628 Hcd586 left 0.26GTCCTGTCTAAAGGAAGAAGTTTGTTCTACTGTAAACAGT 2629 Hcd249 right 0.26CAGGTACATGTTGATCAGCAGGGGCTGGGAGGCGCCGCTC 2630 Hcd689 right 0.27GTACATCTGGATGTAGTTGTGCTGCAGCTGCTTCTGGTAG 2631 mir-194-2No1 0.25TGGTTCCCGCCCCCTGTAACAGCAACTCCATGTGGAAGTG 2632 Hcd581 right 0.26AGGAGATATGCCAAGATATATTCACAGCTTTATATACACA 2633 Hcd270 right 0.3AAATGTTGTTATAGTATCCCACCTACCCTGATGTATCTTT 2634 mir-025-prec 0.27ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 2635 Hcd340 left 0.27GGACAATTCAACAGTGGTGAGTCACTTCGCCACTTTTCAG 2636 mir-007-1-prec 0.27TGTTGGCCTAGTTCTGTGTGGAAGACTAGTGATTTTGTTG 2637 mir-093-prec-7.1 = 093-10.25 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 2638 mir-106-prec-X 0.26CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2639 Hcd794 right 0.27GGCCACCACAGACACCAACAAGTTCAGTCCGTTTCTGCAG 2640 mir-020-prec 0.26TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG 2641 mir-4323p 0.26CCTTACGTGGGCCACTGGATGGCTCCTCCATGTCTTGGAG

TABLE 100 Radiation microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2642 mir-136-precNo2 0.3TGAGCCCTCGGAGGACTCCATTTGTTTTGATGATGGATTC 2643 Hcd570 right 0.26GCCCAACAGAACAACTTGTTTCTCCAGAGCCTGAGGTTTA 2644 Hcd873 left 0.26TCTTCTGACAATGAAGGTAGGCGGACAACGAGGAGATTGC 2645 Hcd282PO right 0.26GAAGACGGACTTGGTTCCGTTTGACCAGCCAGAGCAGGGG 2646 Hcd799 left 0.25GTCCGGCGCGAGTGGAGCTGTTGTAAAATGGCGGCCGAAG 2647 Hcd829 right 0.39AAAATGGCGGCGGGAAAAGCGAGCGGCGAGAGCGAGGAGG 2648 Hcd210_HPR205 right 0.32CGAAACATTCGCGGTGCACTTCTTTTTCAGTATCCTATTC 2649 mir-219-prec 0.26ATTGTCCAAACGCAATTCTCGAGTCTATGGCTCCGGCCGA 2650 mir-202* 0.31CCGCCCGCCGTTCCTTTTTCCTATGCATATACTTCTTTGA 2651 mir-429No2 0.42CACCGCCGGCCGATGGGCGTCTTACCAGACATGGTTAGAC 2652 Hcd693 right 0.32AGGCTTTGTGCGCGCATTAAAGCTCGCCGGACCCCCGACC 2653 mir-022-prec 0.34TGTCCTGACCCAGCTAAAGCTGCCAGTTGAAGAACTGTTG 2654 NPR88 right 0.32CTTACCCTGGTGCGTGGGGCCGCAGGGCTAACACCAAAAA 2655 mir-198-prec 0.39TCATTGGTCCAGAGGGGAGATAGGTTCCTGTGATTTTTCC 2656 mir-199b-precNo1 0.29GTCTGCACATTGGTTAGGCTGGGCTGGGTTAGACCCTCGG 2657 Hcd145 left 0.26AAAAATCCCAGCGGCCACCTTTCCTCCCTGCCCCATTGGG 2658 mir-124a-2-prec 0.34TTAAGGCACGCGGTGAATGCCAAGAGCGGAGCCTACGGCT 2659 mir-138-2-prec 0.39AGCTGGTGTTGTGAATCAGGCCGACGAGCAGCGCATCCTC 2660 Hcd960 left 0.29CTCAGTCTGCGGGCCCCGAGGAGGGTTGTGGGCCCTTTTT 2661 Hcd869 left 0.31CGAGAGGCACTTTGTACTTCTGCCAGGAGACCATATGATA 2662 Hcd384 left 0.41TTACCCAGCCGGGCCGCCAACACCAGATCCTTCTCCTTCT 2663 mir-027b-prec 0.31CCGCTTTGTTCACAGTGGCTAAGTTCTGCACCTGAAGAGA 2664 Hcd444 right 0.31GTATATGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTGT 2665 mir-194-2No1 0.3TGGTTCCCGCCCCCTGTAACAGCAACTCCATGTGGAAGTG 2666 mir-197-prec 0.44TAAGAGCTCTTCACCCTTCACCACCTTCTCCACCCAGCAT 2667 Hcd913 right 0.39CAAACATCATGTGACGTCTGTGGAGCGGCGGCGGCGGCGG 2668 HPR163 left 0.39GCTGCCCCCTCCCTTAGCAACGTGGCCCCGGCGTTCCAAA 2669 mir-138-1-prec 0.25AGCTGGTGTTGTGAATCAGGCCGTTGCCAATCAGAGAACG 2670 mir-010a-precNo1 0.25GTCTGTCTTCTGTATATACCCTGTAGATCCGAATTTGTGT 2671 mir-023b-prec 0.34AATCACATTGCCAGGGATTACCACGCAACCACGACCTTGG 2672 mir-193bNo2 0.35CTGTGGTCTCAGAATCGGGGTTTTGAGGGCGAGATGAGTT 2673 Hcd654 left 0.43AACGAGTAAAAGGCGTACATGGGAGCGCGGGGCGGCAGAG 2674 Hcd542 left 0.26ATCTCAGTAGCCAATATTTTTCTCTGCTGGTATCAAATGA 2675 mir-199a-2-prec 0.28TCGCCCCAGTGTTCAGACTACCTGTTCAGGACAATGCCGT 2676 mir-214-prec 0.43TGTACAGCAGGCACAGACAGGCAGTCACATGACAACCCAG 2677 Hcd608 right 0.31CTTGTGTTTTCACAGCAGCCACAGGCCCTACATCCTTCCT 2678 Hcd684 right 0.28AGAAGGCGCTCCCTGCTAGCCCGGCTCTGTTCTAATTATA 2679 mir-145-prec 0.4CCTCACGGTCCAGTTTTCCCAGGAATCCCTTAGATGCTAA 2680 mir-023a-prec 0.37TCCTGTCACAAATCACATTGCCAGGGATTTCCAACCGACC 2681 mir-024-2-prec 0.32AGTTGGTTTGTGTACACTGGCTCAGTTCAGCAGGAACAGG 2682 mir-199a-1-prec 0.29GCCAACCCAGTGTTCAGACTACCTGTTCAGGAGGCTCTCA

TABLE 101 5-Aza-2′-deoxycytidine (decitabine) microRNA biomarkers. SEQID NO Medianprobe Corr Sequence 2683 mir-096-prec-7No1 0.36CTCCGCTCTGAGCAATCATGTGCAGTGCCAATATGGGAAA 2684 Hcd605 right 0.25GGTTAAGACTCTAACAAACGAGTTGTGAATTGTAGCAATG 2685 mir-20bNo1 0.3AGTACCAAAGTGCTCATAGTGCAGGTAGTTTTGGCATGAC 2686 miR-373*No1 0.26GGGATACTCAAAATGGGGGCGCTTTCCTTTTTGTCTGTAC 2687 HUMTRAB 0.3ATGGTAGAGCGCTCGCTTTGCTTGCGAGAGGTAGCGGGAT 2688 mir-019b-1-prec 0.25TTCTGCTGTGCAAATCCATGCAAAACTGACTGTGGTAGTG 2689 HPR163 left 0.31GCTGCCCCCTCCCTTAGCAACGTGGCCCCGGCGTTCCAAA 2690 mir-371No1 0.25ACTTTCTGCTCTCTGGTGAAAGTGCCGCCATCTTTTGAGT 2691 mir-025-prec 0.29ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 2692 mir-18bNo2 0.27AGCAGCTTAGAATCTACTGCCCTAAATGCCCCTTCTGGCA 2693 mir-093-prec-7.1 = 093-10.28 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 2694 mir-106-prec-X 0.29CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2695 mir-142-prec 0.29CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2696 mir-020-prec 0.29TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 102 Idarubicin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2697 HUMTRF 0.33 GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 2698mir-483No1 0.3 ATCACGCCTCCTCACTCCTCTCCTCCCGTCTTCTCCTCTC 2699 MPR74 left0.27 CAAAGGTCACAATTAACATTCATTGTTGTCGGTGGGTTGT 2700 mir-122a-prec 0.27CCTTAGCAGAGCTGTGGAGTGTGACAATGGTGTTTGTGTC 2701 ath-MIR180aNo2 0.29TGAGAATCTTGATGATGCTGCATCGGCAATCAACGACTAT 2702 mir-128b-precNo1 0.26TCACAGTGAACCGGTCTCTTTCCCTACTGTGTCACACTCC 2703 Hcd923 left 0.25TGGGAACCTTGTTAAAATGCAGATTCTGATTCTCAGGTCT 2704 mir-106-prec-X 0.25CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2705 mir-342No1 0.36GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 2706 mir-142-prec 0.34CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2707 HPR169 right 0.25GTTTCTTTCTCACGGTAACTGGCAGCCTCGTTGTGGGCTG 2708 mir-223-prec 0.36GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 2709 Hcd754 left 0.26TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC 2710 mir-020-prec 0.29TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 103 Melphalan microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2711 mir-124a-3-prec 0.32TTAAGGCACGCGGTGAATGCCAAGAGAGGCGCCTCCGCCG 2712 mir-181a-precNo1 0.28TCAGAGGACTCCAAGGAACATTCAACGCTGTCGGTGAGTT 2713 Hcd773 left 0.26CTTCCTCCCTGGGCATCTCTAGCACAGGGGATCCCCAAAC 2714 Hcd683 left 0.25CTATGACAGAAGGTACTCTGTGGGAGGGAGGAGATAATAG 2715 Hcd796 left 0.29GGTGGGATTACCCGGCTGCCGCTGTCGCCTGGATGGTCTC 2716 HUMTRF 0.44GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 2717 HUMTRS 0.27TCTAGCGACAGAGTGGTTCAATTCCACCTTTCGGGCGCCA 2718 mir-181b-2No1 0.25CTGATGGCTGCACTCAACATTCATTGCTGTCGGTGGGTTT 2719 Hcd294 left 0.26TTATCATAAAATAATCACAGCCCTCAGGTGCTGTGAGGCA 2720 mir-20bNo1 0.27AGTACCAAAGTGCTCATAGTGCAGGTAGTTTTGGCATGAC 2721 mir-181dNo1 0.27GAGGTCACAATCAACATTCATTGTTGTCGGTGGGTTGTGA 2722 mir-213-precNo1 0.4AACATTCATTGCTGTCGGTGGGTTGAACTGTGTGGACAAG 2723 Hcd148_HPR225left 0.29AATTAATGACCAAAATGTCAGATGTGTCCACAGCTAATTA 2724 mir-515-15p 0.34GATCTCATGCAGTCATTCTCCAAAAGAAAGCACTTTCTGT 2725 mir-181b-precNo1 0.43TGAGGTTGCTTCAGTGAACATTCAACGCTGTCGGTGAGTT 2726 Hcd783 left 0.26CAGGCTCACACCTCCCTCCCCCAACTCTCTGGAATGTATA 2727 HUMTRAB 0.29ATGGTAGAGCGCTCGCTTTGCTTGCGAGAGGTAGCGGGAT 2728 HUMTRN 0.27CAATCGGTTAGCGCGTTCGGCTGTTAACCGAAAGGTTGGT 2729 mir-181b-1No1 0.31TTTAAAAGGTCACAATCAACATTCATTGCTGTCGGTGGGT 2730 mir-124a-1-prec1 0.31ATACAATTAAGGCACGCGGTGAATGCCAAGAATGGGGCTG 2731 mir-367No1 0.26TCTGTTGAATATAAATTGGAATTGCACTTTAGCAATGGTG 2732 mir-128b-precNo1 0.38TCACAGTGAACCGGTCTCTTTCCCTACTGTGTCACACTCC 2733 Hcd43 8right 0.25GTGTTTATTTGAATCTCACATCGCTCATAAGAATACACGC 2734 mir-025-prec 0.3ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 2735 mir-216-precNo1 0.35CTGGGATTATGCTAAACAGAGCAATTTCCTAGCCCTCACG 2736 Hcd731 left 0.26AATTGTGACAACTGAGTGGGAGGTTTGTGTGATGATTATC 2737 mir-093-prec-7.1 = 093-10.25 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 2738 mir-106-prec-X 0.27CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2739 mir-342No1 0.36GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 2740 mir-142-prec 0.53CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2741 HSHELA01 0.32GGCCGCAGCAACCTCGGTTCGTATCCGAGTCACGGCACCA 2742 HUMTRV1A 0.25ACGCGAAAGGTCCCCGGTTCGAAACCGGGCGGAAACACCA 2743 mir-223-prec 0.46GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 2744 Hcd754 left 0.45TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC 2745 mir-020-prec 0.3TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 104 IL4-PR3B fusion protein microRNA biomarkers. SEQ ID NOMedianprobe Corr Sequence 2746 Hcd829 right 0.28AAAATGGCGGCGGGAAAAGCGAGCGGCGAGAGCGAGGAGG 2747 mir-197-prec 0.28TAAGAGCTCTTCACCCTTCACCACCTTCTCCACCCAGCAT 2748 HPR163 left 0.28GCTGCCCCCTCCCTTAGCAACGTGGCCCCGGCGTTCCAAA 2749 mir-150-prec 0.47CTCCCCATGGCCCTGTCTCCCAACCCTTGTACCAGTGCTG

TABLE 105 Valproic acid (VPA) microRNA biomarkers. SEQ ID NO MedianprobeCorr Sequence 2750 mir-034precNo1 0.26GAGTGTTTCTTTGGCAGTGTCTTAGCTGGTTGTTGTGAGC 2751 Hcd255 left 0.28CTAGCTCCGTTCGTGATCCGGGAGCCTGGTGCCAGCGAGA 2752 Hcd712 right 0.27GAAGATCGGTTGTCATCTGGTCTGGTCAGCCCGGCCCCGA 2753 Hcd965 left 0.26TGTTAAGTGGAAAAGCCTCCAGGAACGTGGCAGAAAAAGG 2754 Hcd891 right 0.29GCAACGGCCTGATTCACAACACCAGCTGCCCCACCACACC 2755 Hcd210_HPR205 right 0.31CGAAACATTCGCGGTGCACTTCTTTTTCAGTATCCTATTC 2756 mir-429No2 0.33CACCGCCGGCCGATGGGCGTCTTACCAGACATGGTTAGAC 2757 Hcd753 left 0.27GACCTGATTCCCATCTTTGTATTTGGCGACCACCCGACTG 2758 Hcd693 right 0.38AGGCTTTGTGCGCGCATTAAAGCTCGCCGGACCCCCGACC 2759 MPR203 left 0.25CTATATTGGACCGCAGCGCTGAGAGCTTTTGTGTTTAATG 2760 Hcd704 left 0.4TCTGTATTTAATTTGGCTCAGCCGGGAAGATTTTTGGCTC 2761 Hcd863PO right 0.3TTGCAGAGCCTAAGACACAGGCCCAGAGAGGCAGTGATCG 2762 mir-122a-prec 0.29CCTTAGCAGAGCTGTGGAGTGTGACAATGGTGTTTGTGTC 2763 Hcd760 left 0.35TGTGGTCACGTTTCTCCCTCTCTGCTGGCCCCCATCTGTC 2764 Hcd338 left 0.35CTTCTCCTCCTGTTCGCCGCAGGCGCCCGTCCCAGTAGTC 2765 HPR213 right 0.33AACAACTTTGTGCTGGTGCCGGGGAAGTTTGTGTCTCCAA 2766 Hcd852 right 0.26AAAAGTAAACAACAATTTGCCGCTGCCAGCCTCCCATTAG 2767 Hcd366 left 0.28ATACTAGATTAAATTTCAGCCCCGGGCCAATCTGTCAAAG 2768 MPR103 right 0.27GAGGTGTTTGTGCTCCACTCGGCTCCCTTGGTTACATAAC 2769 Hcd669 right 0.27ATGTTTAACAGTCCAGGTTTTGTAGAATATGTGGTGGACC 2770 mir-188-prec 0.27TCACATCCCTTGCATGGTGGAGGGTGAGCTTTCTGAAAAC

TABLE 106 All-trans retinoic acid (ATRA) microRNA biomarkers. SEQ ID NOMedianprobe Corr Sequence 2771 Hcd257 left 0.42CTTCTTGTATAAGCACTGTGCTAAAATTGCAGACACTAGG 2772 mir-148-prec 0.45TGAGTATGATAGAAGTCAGTGCACTACAGAACTTTGTCTC 2773 Hcd512 left 0.28CTGCGCTCTCGGAAATGACTCGCTCCAATCCCGCTTCGCG 2774 HPR227 right 0.25CAGTGCAATGATATTGTCAAAGCATCTGGGACCAGCCTTG 2775 Hcd421 right 0.37AGTAAACAATGTCGGCTTTCCGCCTCCTCCCCTGCCATCC 2776 MPR203 left 0.39CTATATTGGACCGCAGCGCTGAGAGCTTTTGTGTTTAATG 2777 mir-017-precNo1 0.26GCATCTACTGCAGTGAAGGCACTTGTAGCATTATGGTGAC 2778 mir-219-2No1 0.26CTCAGGGGCTTCGCCACTGATTGTCCAAACGCAATTCTTG 2779 mir-328No1 0.3GAAAGTGCATACAGCCCCTGGCCCTCTCTGCCCTTCCGTC 2780 Hcd783 left 0.31CAGGCTCACACCTCCCTCCCCCAACTCTCTGGAATGTATA 2781 Hcd181 left 0.32TTGGCGTCCTTGTCTCTCTCTCCCCTGCCCAGTGGCCTCC 2782 HPR213 right 0.3AACAACTTTGTGCTGGTGCCGGGGAAGTTTGTGTCTCCAA 2783 mir-191-prec 0.31CAACGGAATCCCAAAAGCAGCTGTTGTCTCCAGAGCATTC 2784 mir-375 0.31TTTTGTTCGTTCGGCTCGCGTGAGGCAGGGGCGGCCTCTC 2785 mir-212-precNo2 0.26CGGACAGCGCGCCGGCACCTTGGCTCTAGACTGCTTACTG 2786 Hcd913 right 0.34CAAACATCATGTGACGTCTGTGGAGCGGCGGCGGCGGCGG 2787 Hcd716 right 0.48CAATAAATGTGCCTATAAAGGCGCCGGCTCCGGGGCGCGG 2788 MPR207 right 0.3AACAACTTTGTGCTGGTGCCGGGGAAGTTTGTGTCTCCTA 2789 HPR206 left 0.26CTATATTGGACCGCAGCGCTGAGAGCTTTTGTGTTTAATG 2790 mir-016b-chr3 0.29GTTCCACTCTAGCAGCACGTAAATATTGGCGTAGTGAAAT 2791 Hcd654 left 0.34AACGAGTAAAAGGCGTACATGGGAGCGCGGGGCGGCAGAG 2792 mir-195-prec 0.3TCTAGCAGCACAGAAATATTGGCACAGGGAAGCGAGTCTG 2793 Hcd425 left 0.25GGTTCTACTCTCTTACCCCTCCCCCACGTGGTTGTTGCTG 2794 mir-148aNo1 0.35TGAGTATGATAGAAGTCAGTGCACTACAGAACTTTGTCTC 2795 mir-142-prec 0.36CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2796 mir-016a-chr13 0.25CAATGTCAGCAGTGCCTTAGCAGCACGTAAATATTGGCGT

TABLE 107 Cytoxan microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2797 Hcd99 right 0.25 CAATCCTGGCTGCAGGCATATTTGCATATTGGATGCTGTG2798 mir-520c/526a 0.32 TCTCAGGCTGTCGTCCTCTAGAGGGAAGCACTTTCTGTTG 2799mir-191-prec 0.32 CAACGGAATCCCAAAAGCAGCTGTTGTCTCCAGAGCATTC 2800mir-205-prec 0.35 TCCTTCATTCCACCGGAGTCTGTCTCATACCCAACCAGAT 2801 mir-3750.33 TTTTGTTCGTTCGGCTCGCGTGAGGCAGGGGCGGCCTCTC 2802 mir-423No1 0.29CAAAAGCTCGGTCTGAGGCCCCTCAGTCTTGCTTCCTAAC 2803 mir-449No1 0.39TGTGATGAGCTGGCAGTGTATTGTTAGCTGGTTGAATATG 2804 mir-196-2-precNo2 0.26GCTGATCTGTGGCTTAGGTAGTTTCATGTTGTTGGGATTG

TABLE 108 Topotecan (Hycamtin) microRNA biomarkers. SEQ ID NOMedianprobe Corr Sequence 2805 HUMTRF 0.26GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 2806 MPR74 left 0.29CAAAGGTCACAATTAACATTCATTGTTGTCGGTGGGTTGT 2807 mir-213-precNo1 0.28AACATTCATTGCTGTCGGTGGGTTGAACTGTGTGGACAAG 2808 mir-155-prec 0.31TTAATGCTAATCGTGATAGGGGTTTTTGCCTCCAACTGAC 2809 mir-181b-precNo1 0.31TGAGGTTGCTTCAGTGAACATTCAACGCTGTCGGTGAGTT 2810 mir-342No1 0.33GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 2811 mir-4323p 0.28CCTTACGTGGGCCACTGGATGGCTCCTCCATGTCTTGGAG

TABLE 109 Suberoylanilide hydroxamic acid (SAHA, vorinostat, Zolinza)microRNA biomarkers. SEQ ID NO Medianprobe Corr Sequence 2812mir-092-prec-X = 092-2 0.38 GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG2813 mir-123-precNo1 0.31 GACGGGACATTATTACTTTTGGTACGCGCTGTGACACTTC 2814mir-514-1No2 0.29 TGTCTGTGGTACCCTACTCTGGAGAGTGACAATCATGTAT 2815mir-101-prec-9 0.25 GCTGTATATCTGAAAGGTACAGTACTGTGATAACTGAAGA 2816mir-148-prec 0.36 TGAGTATGATAGAAGTCAGTGCACTACAGAACTTTGTCTC 2817mir-106aNo1 0.34 CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2818mir-20bNo1 0.41 AGTACCAAAGTGCTCATAGTGCAGGTAGTTTTGGCATGAC 2819 Hcd781right 0.32 AGTTTCTTTAATTAATGAAGTTTTTGGGTCTGCTCCACTT 2820 mir-017-precNo20.29 GTCAGAATAATGTCAAAGTGCTTACAGTGCAGGTAGTGAT 2821 mir-019b-2-prec 0.42GTGGCTGTGCAAATCCATGCAAAACTGATTGTGATAATGT 2822 mir-033-prec 0.27GTGGTGCATTGTAGTTGCATTGCATGTTCTGGTGGTACCC 2823 mir-092prec-13 = 092-1No20.28 TCTGTATGGTATTGCACTTGTCCCGGCCTGTTGAGTTTGG 2824 mir-107No1 0.29GGCATGGAGTTCAAGCAGCATTGTACAGGGCTATCAAAGC 2825 mir-103-prec-5 = 103-10.32 TATGGATCAAGCAGCATTGTACAGGGCTATGAAGGCATTG 2826 MPR216 left 0.29GATCCTAGTAGTGCCAAAGTGCTCATAGTGCAGGTAGTTT 2827 mir-29b-2 = 102prec7.1= 7.2 0.27 AGTGATTGTCTAGCACCATTTGAAATCAGTGTTCTTGGGG 2828 mir-019b-1-prec0.4 TTCTGCTGTGCAAATCCATGCAAAACTGACTGTGGTAGTG 2829 mir-107-prec-10 0.3GGCATGGAGTTCAAGCAGCATTGTACAGGGCTATCAAAGC 2830 mir-135-2-prec 0.37CACTCTAGTGCTTTATGGCTTTTTATTCCTATGTGATAGT 2831 Hcd581 right 0.28AGGAGATATGCCAAGATATATTCACAGCTTTATATACACA 2832 mir-103-2-prec 0.29GTAGCATTCAGGTCAAGCAACATTGTACAGGGCTATGAAA 2833 Hcd230 left 0.27CATTCTCTACAAGCATATGGCCTTGGGACATTAAGATGGC 2834 mir-025-prec 0.4ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 2835 mir-208-prec 0.31ACCTGATGCTCACGTATAAGACGAGCAAAAAGCTTGTTGG 2836 mir-18bNo2 0.31AGCAGCTTAGAATCTACTGCCCTAAATGCCCCTTCTGGCA 2837 mir-093-prec-7.1 = 093-10.39 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 2838 mir-106-prec-X 0.48CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2839 mir-142-prec 0.37CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2840 HPR169 right 0.28GTTTCTTTCTCACGGTAACTGGCAGCCTCGTTGTGGGCTG 2841 mir-018-prec 0.44TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC 2842 mir-020-prec 0.48TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 110 Depsipeptide (FR901228) microRNA biomarkers. SEQ ID NOMedianprobe Corr Sequence 2843 Hcd415 right 0.27GATGTTTGGGAAACAATGGGAGTGAGAGAATGGGAGAGCT 2844 mir-147-prec 0.27GACTATGGAAGCCAGTGTGTGGAAATGCTTCTGCTAGATT 2845 mir-033b-prec 0.34GTGCATTGCTGTTGCATTGCACGTGTGTGAGGCGGGTGCA 2846 Hcd778 right 0.34CAGAGGGGAGGCCCAGAGGAGAGGGAAGCTTGGGCAAAGG 2847 mir-127-prec 0.25TCGGATCCGTCTGAGCTTGGCTGGTCGGAAGTCTCATCAT 2848 mir-324No1 0.28TGGAGACCCACTGCCCCAGGTGCTGCTGGGGGTTGTAGTC 2849 Hcd794 right 0.35GGCCACCACAGACACCAACAAGTTCAGTCCGTTTCTGCAG 2850 Hcd634 left 0.27CTGCTCCGCTCAGAGCCTTTTCCTCTCCACTTCCTGTTCA

TABLE 111 Bortezomib microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2851 MPR121 left 0.31 CACCTGGCTCTGAGAACTGAATTCCATAGGCTGTGAGCTC2852 Hcd115 left 0.27 CTCTGTGGCCATTTCGGTTTTTCCAGTCCGATGCCCCTGA 2853Hcd693 right 0.28 AGGCTTTGTGCGCGCATTAAAGCTCGCCGGACCCCCGACC 2854 Hcd704left 0.25 TCTGTATTTAATTTGGCTCAGCCGGGAAGATTTTTGGCTC 2855 HPR100 right0.28 GGTGTTTGTGCTCCACTCAGCTCCCTTGGTTACATAACAG 2856 Hcd760 left 0.26TGTGGTCACGTTTCTCCCTCTCTGCTGGCCCCCATCTGTC 2857 mir-147-prec 0.3GACTATGGAAGCCAGTGTGTGGAAATGCTTCTGCTAGATT 2858 mir-033b-prec 0.29GTGCATTGCTGTTGCATTGCACGTGTGTGAGGCGGGTGCA 2859 mir-146-prec 0.33TGAGAACTGAATTCCATGGGTTGTGTCAGTGTCAGACCTC 2860 Hcd142 right 0.3TAAATGTGTAATTTCTCCCTTGACGGCCCCCGGCCGCTGG 2861 mir-501No2 0.33ATGCAATGCACCCGGGCAAGGATTCTGAGAGGGTGAGCCC 2862 Hcd716 right 0.26CAATAAATGTGCCTATAAAGGCGCCGGCTCCGGGGCGCGG 2863 MPR207 right 0.27AACAACTTTGTGCTGGTGCCGGGGAAGTTTGTGTCTCCTA 2864 Hcd777 left 0.26CAGGTGGGTGCTGAGGCCGCGTTGTTGCTTGAAGCTAGCC 2865 mir-204-precNo2 0.27AGGCTGGGAAGGCAAAGGGACGTTCAATTGTCATCACTGG 2866 mir-146bNo1 0.26CACCTGGCACTGAGAACTGAATTCCATAGGCTGTGAGCTC 2867 Hcd511 right 0.29TACCTCAGAAGCCTCACTCAACCCTCTCCCGCTGAGTCTC 2868 Hcd397 left 0.28GTGTGTATACTTATGTGTGTGTATGTGTGAGTGTGAATAT 2869 MPR130 right 0.33CAATCACAGATAGCACCCCTCACCTTGAGCCCATTTTCAC 2870 Hcd782 left 0.28GGAGCCCTGTCTGCAAAGAGTGGTGCGTGTGCGTGTGTGA 2871 mir-324No2 0.28CTGACTATGCCTCCCCGCATCCCCTAGGGCATTGGTGTAA 2872 Hcd794 right 0.34GGCCACCACAGACACCAACAAGTTCAGTCCGTTTCTGCAG 2873 Hcd739 right 0.29TATTAGCTGAGGGAGGGCTGGAGGCGGCTGCATTCCGACT

TABLE 112 Leukeran microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2874 mir-092prec-X = 092-2 0.39GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG 2875 mir-096-prec-7No1 0.26CTCCGCTCTGAGCAATCATGTGCAGTGCCAATATGGGAAA 2876 mir-123-precNo2 0.32TGTGACACTTCAAACTCGTACCGTGAGTAATAATGCGCCG 2877 MPR249 left 0.26TCGGTTTGGTTCAGCTGGTATGCTTTCCAGTATCTCATTC 2878 HPR232 right 0.28TGAATTATTGCACAATAAATTCATGCCCTGTTGTGTCTTA 2879 mir-101-prec-9 0.4GCTGTATATCTGAAAGGTACAGTACTGTGATAACTGAAGA 2880 mir-106aNo1 0.31CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2881 mir-20bNo1 0.38AGTACCAAAGTGCTCATAGTGCAGGTAGTTTTGGCATGAC 2882 Hcd861 right 0.25AAGGTCTGGATTGATCGTACTGCTTTCTGAAAGGTAAAAA 2883 mir-017-precNo2 0.26GTCAGAATAATGTCAAAGTGCTTACAGTGCAGGTAGTGAT 2884 mir-019b-2-prec 0.33GTGGCTGTGCAAATCCATGCAAAACTGATTGTGATAATGT 2885 mir-033-prec 0.3GTGGTGCATTGTAGTTGCATTGCATGTTCTGGTGGTACCC 2886 Hcd102 left 0.26ACTGGAATTATGTTTTATCTTAAGTCCACACTGGATCCTC 2887 MFR216 left 0.32GATCCTAGTAGTGCCAAAGTGCTCATAGTGCAGGTAGTTT 2888 Hcd975 left 0.25GGTTTTGTGTTTTTGTAAACAGCAGAAGGTATTAGTCCAT 2889 mir-019b-1-prec 0.3TTCTGCTGTGCAAATCCATGCAAAACTGACTGTGGTAGTG 2890 mir-135-2-prec 0.38CACTCTAGTGCTTTATGGCTTTTTATTCCTATGTGATAGT 2891 Hcd581 right 0.26AGGAGATATGCCAAGATATATTCACAGCTTTATATACACA 2892 Hcd536_HPR104 right 0.25GCTGCTCTGCTGAGGGGCTGGACTCTGTCCAGAAGCACCA 2893 mir-128b-precNo2 0.25GGGGGCCGATACACTGTACGAGAGTGAGTAGCAGGTCTCA 2894 HSTRNL 0.37TCCGGATGGAGCGTGGGTTCGAATCCCACTTCTGACACCA 2895 mir-025-prec 0.47ACGCTGCCCTGGGCATTGCACTTCTCTCGGTCTGACAGTG 2896 mir-18bNo2 0.27AGCAGCTTAGAATCTACTGCCCTAAATGCCCCTTCTGGCA 2897 HPR262 left 0.26TCAGTTTGGTTCAGCTGGTATGCTTTCCAGTATCTCATTC 2898 Hcd923 right 0.33CTGGAGATAATGATTCTGCATTTCTAATTAACTCCCAGGT 2899 Hcd434 right 0.3CACTTTTTCCTTTGTGGAAATCCTGGGTGACATCACCTCC 2900 Hcd658 right 0.28GACTGCAGAGCAAAAGACACGATGGGTGTCTATTGTTTTC 2901 HPR129 left 0.29TTTTCCTGCTTGATTTGCTTAATGGAAGCTGACAGTGAAG 2902 mir-380-5p 0.32AGGTACCTGAAAAGATGGTTGACCATAGAACATGCCCTAT 2903 mir-093-prec-7.1 = 093-10.45 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 2904 mir-106-prec-X 0.5CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2905 Hcd627 left 0.31GCATTAGGGAGAATAGTTGATGGATTACAAATCTCTGCAT 2906 mir-142-prec 0.33CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2907 mir-018-prec 0.46TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC 2908 mir-020-prec 0.5TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 113 Fludarabine microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2909 Hcd773 left 0.26 CTTCCTCCCTGGGCATCTCTAGCACAGGGGATCCCCAAAC2910 Hcd248 right 0.33 CATTATGCAAATGGTATGAGAGGAAAATTAGGCAATAAGG 2911mir-181dNo1 0.34 GAGGTCACAATCAACATTCATTGTTGTCGGTGGGTTGTGA 2912 MPR74left 0.3 CAAAGGTCACAATTAACATTCATTGTTGTCGGTGGGTTGT 2913 mir-213-precNo10.37 AACATTCATTGCTGTCGGTGGGTTGAACTGTGTGGACAAG 2914 mir-155-prec 0.32TTAATGCTAATCGTGATAGGGGTTTTTGCCTCCAACTGAC 2915 MPR197 right 0.29TATTTATTACAAGGTCCTTCTTCCCCGTAAAACTTTGTCC 2916 mir-181b-precNo1 0.26TGAGGTTGCTTCAGTGAACATTCAACGCTGTCGGTGAGTT 2917 mir-29b-2 = 102prec7.1= 7.2 0.32 AGTGATTGTCTAGCACCATTTGAAATCAGTGTTCTTGGGG 2918 mir-029c-prec0.33 TTTTGTCTAGCACCATTTGAAATCGGTTATGATGTAGGGG 2919 Hcd318 right 0.32CAAGTGGTTAATTGAGCCCACAAGTGACCTACTCAATCAG 2920 mir-128b-precNo1 0.25TCACAGTGAACCGGTCTCTTTCCCTACTGTGTCACACTCC 2921 mir-130a-precNo2 0.27TGTCTGCACCTGTCACTAGCAGTGCAATGTTAAAAGGGCA 2922 mir-140No2 0.26TTCTACCACAGGGTAGAACCACGGACAGGATACCGGGGCA 2923 mir-16-2No1 0.31GTTCCACTCTAGCAGCACGTAAATATTGGCGTAGTGAAAT 2924 mir-526a-2No1 0.26GATCTCGTGCTGTGACCCTCTAGAGGGAAGCACTTTCTGT 2925 mir-016b-chr3 0.3GTTCCACTCTAGCAGCACGTAAATATTGGCGTAGTGAAAT 2926 mir-195-prec 0.34TCTAGCAGCACAGAAATATTGGCACAGGGAAGCGAGTCTG 2927 mir-216-precNo1 0.25CTGGGATTATGCTAAACAGAGCAATTTCCTAGCCCTCACG 2928 mir-342No1 0.26GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 2929 mir-29b-1No1 0.34AGTGATTGTCTAGCACCATTTGAAATCAGTGTTCTTGGGG 2930 Hcd627 left 0.33GCATTAGGGAGAATAGTTGATGGATTACAAATCTCTGCAT 2931 mir-102-prec-1 0.33TCTTTGTATCTAGCACCATTTGAAATCAGTGTTTTAGGAG 2932 mir-142-prec 0.32CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2933 mir-223-prec 0.34GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 2934 let-7f-2-prec2 0.26TGAGGTAGTAGATTGTATAGTTTTAGGGTCATACCCCATC 2935 mir-016a-chr13 0.36CAATGTCAGCAGTGCCTTAGCAGCACGTAAATATTGGCGT

TABLE 114 Vinblastine microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2936 Hcd794 right 0.33 GGCCACCACAGACACCAACAAGTTCAGTCCGTTTCTGCAG2937 Hcd754 left 0.25 TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC

TABLE 115 Busulfan microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2938 mir-096-prec-7No2 0.27TGGCCGATTTTGGCACTAGCACATTTTTGCTTGTGTCTCT 2939 mir-124a-3-prec 0.25TTAAGGCACGCGGTGAATGCCAAGAGAGGCGCCTCCGCCG 2940 mir-101-prec-9 0.25GCTGTATATCTGAAAGGTACAGTACTGTGATAACTGAAGA 2941 Hcd712 right 0.27GAAGATCGGTTGTCATCTGGTCTGGTCAGCCCGGCCCCGA 2942 Hcd693 right 0.26AGGCTTTGTGCGCGCATTAAAGCTCGCCGGACCCCCGACC 2943 mir-219-2No1 0.25CTCAGGGGCTTCGCCACTGATTGTCCAAACGCAATTCTTG 2944 Hcd145 left 0.29AAAAATCCCAGCGGCCACCTTTCCTCCCTGCCCCATTGGG 2945 mir-155-prec 0.29TTAATGCTAATCGTGATAGGGGTTTTTGCCTCCAACTGAC 2946 HPR213 right 0.3AACAACTTTGTGCTGGTGCCGGGGAAGTTTGTGTCTCCAA 2947 mir-212-precNo2 0.34CGGACAGCGCGCCGGCACCTTGGCTCTAGACTGCTTACTG 2948 Hcd913 right 0.33CAAACATCATGTGACGTCTGTGGAGCGGCGGCGGCGGCGG 2949 Hcd716 right 0.51CAATAAATGTGCCTATAAAGGCGCCGGCTCCGGGGCGCGG 2950 MFR207 right 0.26AACAACTTTGTGCTGGTGCCGGGGAAGTTTGTGTCTCCTA 2951 Hcd559 right 0.33TTCTTTGTCTATACATTTCCTAGATTTCTATGCAGTTGGG 2952 Hcd654 left 0.28AACGAGTAAAAGGCGTACATGGGAGCGCGGGGCGGCAGAG 2953 Hcd739 right 0.27TATTAGCTGAGGGAGGGCTGGAGGCGGCTGCATTCCGACT 2954 mir-142-prec 0.4CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG

TABLE 116 Dacarbazine microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2955 mir-092-prec-X = 092-2 0.25GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG 2956 mir-123-precNo2 0.28TGTGACACTTCAAACTCGTACCGTGAGTAATAATGCGCCG 2957 mir-101-prec-9 0.29GCTGTATATCTGAAAGGTACAGTACTGTGATAACTGAAGA 2958 Hcd517 right 0.3GAGGGATTACAGATTAACTCCCACTTCTCCAGACTCAGAA 2959 Hcd796 left 0.37GGTGGGATTACCCGGCTGCCGCTGTCGCCTGGATGGTCTC 2960 Hcd749 right 0.28CGAGGAGGAGGTGACTGCTGTGGATGGTTATGAGACAGAC 2961 Hcd674 left 0.25CTCCAGTGTGGTGTGCCTGCCCCCTTCCGTCATTGCTGTG 2962 mir-019b-2-prec 0.27GTGGCTGTGCAAATCCATGCAAAACTGATTGTGATAATGT 2963 mir-033-prec 0.29GTGGTGCATTGTAGTTGCATTGCATGTTCTGGTGGTACCC 2964 mir092-prec-13 = 092-1No20.33 TCTGTATGGTATTGCACTTGTCCCGGCCTGTTGAGTTTGG 2965 mir-124a-2-prec 0.29TTAAGGCACGCGGTGAATGCCAAGAGCGGAGCCTACGGCT 2966 mir-143-prec 0.36CTGGTCAGTTGGGAGTCTGAGATGAAGCACTGTAGCTCAG 2967 mir-516-43p 0.28AAAGAAAAGAAAGTGCTTCCTTTCAGAGGGTTACTCTTTG 2968 mir-216-precNo1 0.31CTGGGATTATGCTAAACAGAGCAATTTCCTAGCCCTCACG 2969 Hcd731 left 0.26AATTGTGACAACTGAGTGGGAGGTTTGTGTGATGATTATC 2970 mir-106-prec-X 0.26CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2971 mir-142-prec 0.48CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2972 mir-223-prec 0.48CAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 2973 Hcd754 left 0.32TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC 2974 mir-018-prec 0.27TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC

TABLE 117 Oxaliplatin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 2975 mir-092-prec-X = 092-2 0.36GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG 2976 mir-148-prec 0.27TGAGTATGATAGAAGTCAGTGCACTACAGAACTTTGTCTC 2977 mir-20bNo1 0.27AGTACCAAAGTGCTCATAGTGCAGGTAGTTTTGGCATGAC 2978 mir-007-2-precNo2 0.28GGACCGGCTGGCCCCATCTGGAAGACTAGTGATTTTGTTG 2979 mir-017-precNo2 0.28GTCAGAATAATGTCAAAGTGCTTACAGTGCAGGTAGTGAT 2980 mir-019b-2-prec 0.32GTGGCTGTGCAAATCCATGCAAAACTGATTGTGATAATGT 2981 Hcd760 left 0.27TGTGGTCACGTTTCTCCCTCTCTGCTGGCCCCCATCTGTC 2982 Hcd783 left 0.36CAGGCTCACACCTCCCTCCCCCAACTCTCTGGAATGTATA 2983 MPR216 left 0.26GATCCTAGTAGTGCCAAAGTGCTCATAGTGCAGGTAGTTT 2984 mir-375 0.33TTTTGTTCGTTCGGCTCGCGTGAGGCAGGGGCGGCCTCTC 2985 mir-019b-1-prec 0.36TTCTGCTGTGCAAATCCATGCAAAACTGACTGTGGTAGTG 2986 mir-135-2-prec 0.32CACTCTAGTGCTTTATGGCTTTTTATTCCTATGTGATAGT 2987 mir-150-prec 0.25CTCCCCATGGCCCTGTCTCCCAACCCTTGTACCAGTGCTG 2988 mir-128b-precNo1 0.33TCACAGTGAACCGGTCTCTTTCCCTACTGTGTCACACTCC 2989 mir-499No2 0.26GTGAACATCACAGCAAGTCTGTGCTGCTTCCCGTCCCTAC 2990 mir-025-prec 0.38ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 2991 mir-007-1-prec 0.32TGTTGGCCTAGTTCTGTGTGGAAGACTAGTGATTTTGTTG 2992 mir-019a-prec 0.33TGTAGTTGTGCAAATCTATGCAAAACTGATGGTGGCCTGC 2993 mir-093-prec-7.1 = 093-10.46 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 2994 mir-106-prec-X 0.45CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 2995 mir-142-prec 0.41CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 2996 HPR169 right 0.34GTTTCTTTCTCACGGTAACTGGCAGCCTCGTTGTGGGCTG 2997 mir-018-prec 0.4TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC 2998 mir-020-prec 0.44TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG 2999 mir-484 0.33GTCAGGCTCAGTCCCCTCCCGATAAACCCCTAAATAGGGA

TABLE 118 Hydroxyurea microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3000 Hcd257 left 0.34 CTTCTTGTATAAGCACTGTGCTAAAATTGCAGACACTAGG3001 Hcd768 right 0.26 GCCCTGGCGGAACGCTGAGAAGACAGTCGAACTTGACTAT 3002Hcd796 left 0.25 GGTGGGATTACCCGGCTGCCGCTGTCGCCTGGATGGTCTC 3003 HUMTRF0.48 GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 3004 HUMTRS 0.3TCTAGCGACAGAGTGGTTCAATTCCACCTTTCGGGCGCCA 3005 MPR74 left 0.28CAAAGGTCACAATTAACATTCATTGTTGTCGGTGGGTTGT 3006 mir-213-precNo1 0.29AACATTCATTGCTGTCGGTGGGTTGAACTGTCTGGACAAG 3007 mir-155-prec 0.35TTAATGCTAATCGTGATAGGGGTTTTTGCCTCCAACTGAC 3008 Hcd763 right 0.25GGTGCACTCTAAATTCCTGTCCCTGCGGAAGGCTGACTAA 3009 mir-181b-precNo1 0.28TGAGGTTGCTTCAGTGAACATTCAACGCTGTCGGTGAGTT 3010 ath-MIR180aNo2 0.26TGAGAATCTTGATGATGCTGCATCGGCAATCAACGACTAT 3011 mir-216-precNo1 0.37CTGGGATTATGCTAAACAGAGCAATTTCCTAGCCCTCACG 3012 mir-342No1 0.31GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 3013 mir-142-prec 0.49CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 3014 HSHELA01 0.31GGCCGCAGCAACCTCGGTTCGTATCCGAGTCACGGCACCA 3015 HUMTRV1A 0.26ACGCGAAAGGTCCCCGGTTCGAAACCGGGCGGAAACACCA 3016 mir-223-prec 0.59CAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 3017 Hcd754 left 0.46TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC 3018 mir-020-prec 0.26TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 119 Tegafur microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3019 Hcd257 right 0.26 CTTGGTTTTTGCAATAATGCTAGCAGAGTACACACAAGAA3020 Hcd946 left 0.26 CACAGGATTTCAGGGGAGAAACGGTGGATTTTCACAAGAG 3021Hcd503 left 0.3 GAGATGAGGTAGCTGCCAGGTGCCATGGGGGTATAGGTGA 3022 mir-429No10.25 CTAATACTGTCTGGTAAAACCGTCCATCCGCTGCCTGATC 3023 Hcd693 right 0.32AGGCTTTGTGCGCGCATTAAAGCTCGCCGGACCCCCGACC 3024 miR-373*No1 0.33GGGATACTCAAAATGGGGGCGCTTTCCTTTTTGTCTGTAC 3025 Hcd738 left 0.28GAAAAACTTAAGATTCCCTCTCGGCCCTCATTTTTAGCTG 3026 mir-328No1 0.33GAAAGTGCATACAGCCCCTGGCCCTCTCTGCCCTTCCGTC 3027 Hcd783 left 0.36CAGGCTCACACCTCCCTCCCCCAACTCTCTGGAATGTATA 3028 Hcd181 right 0.34GCTCACTGGGCAGGAGCCCTAATCGGATTCGACAGCTGAG 3029 Hcd631 left 0.38CAGATATTTTCTCAGGCAATCCTCAGCCACAGCCTTCTTG 3030 Hcd279 left 0.25CGGACTAACACTCCGCGGGTGTTTCCATGGAGACCGAGGC 3031 mir-194-2No1 0.3TGGTTCCCGCCCCCTGTAACAGCAACTCCATGTGGAAGTG 3032 mir-197-prec 0.38TAAGAGCTCTTCACCCTTCACCACCTTCTCCACCCAGCAT 3033 HPR163 left 0.39GCTGCCCCCTCCCTTAGCAACGTGGCCCCGGCGTTCCAAA 3034 mir-150-prec 0.32CTCCCCATGGCCCTGTCTCCCAACCCTTGTACCAGTGCTG 3035 Hcd323 left 0.26GTTGTAGCATGTGGTTGTATTAATGAACGTTACAGGAGAG 3036 mir-103-2-prec 0.28GTAGCATTCAGGTCAAGCAACATTGTACAGGGCTATGAAA 3037 Hcd243 right 0.27TATTATACATCATTTCCCATCAATCGACGAACTAAAGCCT 3038 Hcd938 right 0.27ATTCCCTGCATCACTCTCATGAAATGGCTGAGAAAGTGAG 3039 mir-025-prec 0.29ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 3040 mir-007-1-prec 0.36TGTTGGCCTAGTTCTGTGTGGAAGACTAGTGATTTTGTTG 3041 MPR243 left 0.26GTATTTACCTAGTTGTAATGTGGGTTGCCATGGTGTTTTG 3042 Hcd511 right 0.27TACCTCAGAAGCCTCACTCAACCCTCTCCCGCTGAGTCTC 3043 Hcd654 left 0.26AACGAGTAAAAGGCGTACATGGGAGCGCGGGGCGGCAGAG 3044 mir-199a-2-prec 0.3TCGCCCCAGTGTTCAGACTACCTGTTCAGGACAATGCCGT 3045 mir-214-prec 0.27TGTACAGCAGGCACAGACAGGCAGTCACATGACAACCCAG 3046 mir-093-prec-7.1 = 093-10.33 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 3047 mir-106-prec-X 0.27CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 3048 Hcd794 right 0.41GGCCACCACAGACACCAACAAGTTCAGTCCGTTTCTGCAG 3049 Hcd530 right 0.26AAGGAAAATCAAACCCACAATGCTGAACACAACAATGACC 3050 HSHELA01 0.34GGCCGCAGCAACCTCGGTTCGTATCCGAGTCACGGCACCA 3051 Hcd754 left 0.29TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC 3052 mir-020-prec 0.29TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 120 Daunorubicin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3053 Hcd768 right 0.25 GCCCTGGCGGAACGCTGAGAAGACAGTCGAACTTGACTAT3054 HUMTRF 0.34 GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 3055 Hcd145left 0.28 AAAAATCCCAGCGGCCACCTTTCCTCCCTGCCCCATTGGG 3056 Hcd923 right0.27 CTGGAGATAATGATTCTGCATTTCTAATTAACTCCCAGGT 3057 mir-216-precNo1 0.27CTGGGATTATGCTAAACAGAGCAATTTCCTAGCCCTCACG 3058 mir-093-prec-7.1 = 093-10.25 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 3059 mir-342No1 0.33GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 3060 Hcd794 right 0.28GGCCACCACAGACACCAACAAGTTCAGTCCGTTTCTGCAG 3061 mir-142-prec 0.48CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 3062 HSHELA01 0.3GGCCGCAGCAACCTCGGTTCGTATCCGAGTCACGGCACCA 3063 mir-223-prec 0.33GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 3064 Hcd754 left 0.32TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC

TABLE 121 Bleomycin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3065 mir-125b-2-precNo2 0.29ACCAGACTTTTCCTAGTCCCTGAGACCCTAACTTGTGAGG 3066 mir-022-prec 0.26TGTCCTGACCCAGCTAAAGCTGCCAGTTGAAGAACTGTTG 3067 mir-125b-1 0.29TCCCTGAGACCCTAACTTGTGATGTTTACCGTTTAAATCC 3068 mir-155-prec 0.38TTAATGCTAATCGTGATAGGGGTTTTTGCCTCCAACTGAC 3069 mir-100No1 0.25CCTGTTGCCACAAACCCGTAGATCCGAACTTGTGGTATTA 3070 mir-409-3p 0.27GACGAATGTTGCTCGGTGAACCCCTTTTCGGTATCAAATT 3071 mir-495No1 0.31GTGACGAAACAAACATGGTGCACTTCTTTTTCGGTATCAA 3072 mir-199a-2-prec 0.29TCGCCCCAGTGTTCAGACTACCTGTTCAGGACAATGCCGT 3073 mir-382 0.28GGTACTTGAAGAGAAGTTGTTCGTGGTGGATTCGCTTTAC 3074 mir-100-1/2-prec 0.26TGAGGCCTGTTGCCACAAACCCGTAGATCCGAACTTGTGG

TABLE 122 Estramustine microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3075 Hcd338 left 0.32 CTTCTCCTCCTGTTCGCCGCAGGCGCCCGTCCCAGTAGTC3076 mir-099b-prec-19No1 0.25 GCCTTCGCCGCACACAAGCTCGTGTCTGTGGGTCCGTGTC3077 mir-149-prec 0.34 CGAGCTCTGGCTCCGTGTCTTCACTCCCGTGCTTGTCCGA

TABLE 123 Chlorambucil microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3078 mir-181a-precNo1 0.26TCAGAGGACTCCAAGGAACATTCAACGCTGTCGGTGAGTT 3079 mir-181c-precNo1 0.25TGCCAAGGGTTTGGGGGAACATTCAACCTGTCGGTGAGTT 3080 HUMTRF 0.35GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 3081 mir-181dNo1 0.26GAGGTCACAATCAACATTCATTGTTGTCGGTGGGTTGTGA 3082 MPR74 left 0.28CAAAGGTCACAATTAACATTCATTGTTGTCGGTGGGTTGT 3083 Hcd817 left 0.28TAATGAGAATTATGTTTGCACATTGAGGCAGGATAAATCC 3084 mir-213-precNo1 0.42AACATTCATTGCTGTCGGTGGGTTGAACTGTGTGGACAAG 3085 mir-155-prec 0.33TTAATGCTAATCGTGATAGGGGTTTTTGCCTCCAACTGAC 3086 Hcd148_HPR225left 0.29AATTAATGACCAAAATGTCAGATGTGTCCACAGCTAATTA 3087 mir-515-15p 0.27GATCTCATGCAGTCATTCTCCAAAAGAAAGCACTTTCTGT 3088 mir-181b-precNo1 0.41TGAGGTTGCTTCAGTGAACATTCAACGCTGTCGGTGAGTT 3089 HUMTRN 0.27CAATCGGTTAGCGCGTTCGGCTGTTAACCGAAAGGTTGGT 3090 mir-128b-precNo1 0.37TCACAGTGAACCGGTCTCTTTCCCTACTGTGTCACACTCC 3091 mir-450-2No1 0.29GAAAGATGCTAAACTATTTTTGCGATGTGTTCCTAATATG 3092 mir-216-precNo1 0.29CTGGGATTATGCTAAACAGAGCAATTTCCTAGCCCTCACG 3093 mir-342No1 0.35GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 3094 mir-142-prec 0.45CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 3095 mir-223-prec 0.39GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 3096 Hcd754 left 0.37TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC 3097 mir-020-prec 0.28TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 124 Mechlorethamine microRNA biomarkers. SEQ ID NO MedianprobeCorr Sequence 3098 mir-124a-3-prec 0.33TTAAGGCACGCGGTGAATGCCAAGAGAGGCGCCTCCGCCG 3099 Hcd946 left 0.3CACAGGATTTCAGGGGAGAAACGGTGGATTTTCACAAGAG 3100 Hcd683 left 0.29CTATGACAGAAGGTACTCTGTGGGAGGGAGGAGATAATAG 3101 HPR264 right 0.25CAAATGGCGCATCAATGACTATCGCTCTTACAAAGCTCTT 3102 MPR185 right 0.3CAGAACATGCAATGCAACTACAATGCACCACAGCTGCCCG 3103 HUMTRF 0.37GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 3104 Hcd294 left 0.25TTATCATAAAATAATCACAGCCCTCAGGTGCTGTGAGGCA 3105 Hcd503 left 0.27GAGATGAGGTAGCTGCCAGGTGCCATGGGGGTATAGGTGA 3106 mir-20bNo1 0.27AGTACCAAAGTGCTCATAGTGCAGGTAGTTTTGGCATGAC 3107 MPR74 left 0.25CAAAGGTCACAATTAACATTCATTGTTGTCGGTGGGTTGT 3108 MPR234 right 0.28GCTGACGTCACGGGCAGAATTGTCCCATTTAGGGATCCCG 3109 Hcd447 right 0.26CTCAGGCCATTAACCTCAGTTGGTCACTAATCCCTAGGAA 3110 Hcd817 right 0.3GAATCTTGCCCTTGGATGCATACTGTAATTTCCATTAAAG 3111 Hcd148_HPR225left 0.32AATTAATGACCAAAATGTCAGATGTGTCCACAGCTAATTA 3112 mir-515-15p 0.29GATCTCATGCAGTCATTCTCCAAAAGAAAGCACTTTCTGT 3113 Hcd383 right 0.25CTGATAGTACACGGGGCCAAAATAGATGTATGCTTCTAAG 3114 mir-181b-precNo2 0.31ACCATCGACCGTTGATTGTACCCTATGGCTAACCATCATC 3115 Hcd783 left 0.33CAGGCTCACACCTCCCTCCCCCAACTCTCTGGAATGTATA 3116 MPR224 left 0.34TGAGGCCCTCTAGGCCGTGAATTAATGTGTCATAACTCAC 3117 HPR172 right 0.28GTTTAAACAGCCAGTGCAAACATTTAGATCTGAGTCAAAA 3118 MPR216 left 0.32GATCCTAGTAGTGCCAAAGTGCTCATAGTGCAGGTAGTTT 3119 HUMTRN 0.28CAATCGGTTAGCGCGTTCGGCTGTTAACCGAAAGGTTGGT 3120 mir-321No1 0.3TTGGCCTCCTAAGCCAGGGATTGTGGGTTCGAGTCCCACC 3121 HFR159 left 0.25TCCGTCACTTGAACTGGCTGCCAGCGTTCACAGACAGCTG 3122 MPR228 left 0.29TTTTTGCTCCCAGTCAGTAGGAAGATTGTTTCAAATCTGT 3123 ath-MIR180aNo2 0.31TGAGAATCTTGATGATGCTGCATCGGCAATCAACGACTAT 3124 mir-197-prec 0.28TAAGAGCTCTTCACCCTTCACCACCTTCTCCACCCAGCAT 3125 mir-124a-1-prec1 0.26ATACAATTAAGGCACGCGGTGAATGCCAAGAATGGGGCTG 3126 mir-128b-precNo1 0.31TCACAGTGAACCGGTCTCTTTCCCTACTGTGTCACACTCC 3127 Hcd28_HPR39left 0.28CTGACTTTCAGTTCCTATTTAAAATGTCTGAATTGGGAGC 3128 Hcd889 right 0.25ATGCCTTGTGCTCTGTGCTAATTCAGAAGAATAAGCCTGT 3129 Hcd350 right 0.26TAGCACTTAGCAGGTTGTATTATCATTGTCCGTGTCTATG 3130 mir-025-prec 0.31ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 3131 mir-208-prec 0.27ACCTGATGCTCACGTATAAGACGAGCAAAAAGCTTGTTGG 3132 mir-450-2No1 0.25GAAAGATGCTAAACTATTTTTGCGATGTGTTCCTAATATG 3133 Hcd923 right 0.29CTGGAGATAATGATTCTGCATTTCTAATTAACTCCCAGGT 3134 Hcd434 right 0.28CACTTTTTCCTTTGTGGAAATCCTGGGTGACATCACCTCC 3135 HPR129 left 0.27TTTTCCTGCTTGATTTGCTTAATGGAAGCTGACAGTGAAG 3136 HPR220 left 0.27GGAGACACTGTAACAACATTTTACTCCTGACTGATTACAT 3137 mir-380-5p 0.3AGGTACCTGAAAAGATGGTTGACCATAGAACATGCGCTAT 3138 mir-093-prec-7.1 = 093-10.29 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 3139 mir-106-prec-X 0.3CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 3140 mir-342No1 0.28GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 3141 mir-142-prec 0.45CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 3142 HSHELA01 0.29GGCCGCAGCAACCTCGGTTCGTATCCGAGTCACGGCACCA 3143 mir-223-prec 0.32GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 3144 Hcd754 left 0.32TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC 3145 mir-020-prec 0.37TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG 3146 mir-4323p 0.26CCTTACGTGGGCCACTGGATGGCTCCTCCATGTCTTGGAG

TABLE 125 Streptozocin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3147 mir-483No1 0.2 ATCACGCCTCCTCACTCCTCTCCTCCCGTCTTCTCCTCTC3148 Hcd631 right 0.21 AAAACCAAATGGCTGGCTACTCATGTACTGTTGAATGTCT 3149mir-212-precNo1 0.24 CCTCAGTAACAGTCTCCAGTCACGGCCACCGACGCCTGGC 3150Hcd938 right 0.21 ATTCCCTGCATCACTCTCATGAAATGGCTGAGAAAGTGAG 3151 MPR133right 0.2 CTGTAGATACTTTCTCCCTGAGCCCCTCCTGCCCCCCTGC 3152 Hcd794 right0.21 GGCCACCACAGACACCAACAAGTTCAGTCCGTTTCTGCAG 3153 Hcd438 left 0.24GTTTATTTGAATGTGTGATGGGGAGGTCATCAAAATGAAC 3154 Hcd886 right 0.23CTCCAGTTGGGGGTGGGGAGTTGGGAACAGTGTGAATGGG

TABLE 126 Carmustine microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3155 mir-092-prec-X = 092-2 0.33GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG 3156 Hcd517 right 0.33GAGGGATTACAGATTAACTCCCACTTCTCCAGACTCAGAA 3157 Hcd796 left 0.28GGTGGGATTACCCGGCTGCCGCTGTCGCCTGGATGGTCTC 3158 HUMTRF 0.33GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 3159 mir-20bNo1 0.29AGTACCAAAGTGCTCATAGTGCAGGTAGTTTTGGCATGAC 3160 mir-019b-2-prec 0.25GTGGCTGTGCAAATCCATGCAAAACTGATTGTGATAATGT 3161 mir-033-prec 0.27GTGGTGCATTGTAGTTGCATTGCATGTTCTGGTGGTACCC 3162 mir-092-prec-13 = 092-1No20.33 TCTGTATGGTATTGCACTTGTCCCGGCCTGTTGAGTTTGG 3163 Hcd148_HPR225left0.27 AATTAATGACCAAAATGTCAGATGTGTCCACAGCTAATTA 3164 HUMTRAB 0.3ATGGTAGAGCGCTCGCTTTGCTTGCGAGAGGTAGCGGGAT 3165 Hcd975 left 0.26GGTTTTGTGTTTTTGTAAACAGCAGAAGGTATTAGTCCAT 3166 mir-135-2-prec 0.28CACTCTAGTGCTTTATGGCTTTTTATTCCTATGTGATAGT 3167 mir-128b-precNo1 0.27TCACAGTGAACCGGTCTCTTTCCCTACTGTGTCACACTCC 3168 mir-143-prec 0.32CTGGTCAGTTGGGAGTCTGAGATGAAGCACTGTAGCTCAG 3169 mir-025-prec 0.33ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 3170 mir-216-precNo1 0.34CTGGGATTATGCTAAACAGAGCAATTTCCTAGCCCTCACG 3171 mir-093-prec-7.1 = 093-10.3 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 3172 mir-106-prec-X 0.33CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 3173 mir-142-prec 0.61CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 3174 HSHELA01 0.26GGCCGCAGCAACCTCGGTTCGTATCCGAGTCACGGCACCA 3175 HUMTRV1A 0.26ACGCGAAAGGTCCCCGGTTCGAAACCGGGCGGAAACACCA 3176 mir-223-prec 0.52GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 3177 Hcd754 left 0.46TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC 3178 mir-018-prec 0.34TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC 3179 mir-020-prec 0.35TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 127 Lornustine microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3180 mir-101-prec-9 0.27GCTGTATATCTGAAAGGTACAGTACTGTGATAACTGAAGA 3181 Hcd796 left 0.26GGTGGGATTACCCGGCTGCCGCTGTCGCCTGGATGGTCTC 3182 mir-20bNo1 0.28AGTACCAAAGTGCTCATAGTGCAGGTAGTTTTGGCATGAC 3183 HUMTRAB 0.35ATGGTAGAGCGCTCGCTTTGCTTGCGAGAGGTAGCGGGAT 3184 mir-135-2-prec 0.27CACTCTAGTGCTTTATGGCTTTTTATTCCTATGTGATAGT 3185 mir-153-1-prec1 0.32CAGTTGCATAGTCACAAAAGTGATCATTGGCAGGTGTGGC 3186 mir-025-prec 0.29ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 3187 mir-093-prec-7.1 = 093-10.26 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 3188 mir-106-prec-X 0.31CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 3189 mir-142-prec 0.41CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 3190 HUMTRV1A 0.28ACGCGAAAGGTCCCCGGTTCGAAACCGGGCGGAAACACCA 3191 Hcd754 left 0.35TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC 3192 mir-018-prec 0.27TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC 3193 mir-020-prec 0.28TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 128 Mercaptopurine microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3194 mir-092-prec-X = 092-2 0.39GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG 3195 mir-096-prec-7No1 0.26CTCCGCTCTGAGCAATCATGTGCAGTGCCAATATGGGAAA 3196 mir-123-precNo2 0.32TGTGACACTTCAAACTCGTACCGTGAGTAATAATGCGCCG 3197 MPR249 left 0.26TCGGTTTGGTTCAGCTGGTATGCTTTCCAGTATCTCATTC 3198 HPR232 right 0.28TGAATTATTGCACAATAAATTCATGCCCTGTTGTGTCTTA 3199 mir-101-prec-9 0.4GCTGTATATCTGAAAGGTACAGTACTGTGATAACTGAAGA 3200 mir-106aNo1 0.31CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 3201 mir-20bNo1 0.38AGTACCAAAGTGCTCATAGTGCAGGTAGTTTTGGCATGAC 3202 Hcd861 right 0.25AAGGTCTGGATTGATCGTACTGCTTTCTGAAAGGTAAAAA 3203 mir-017-precNo2 0.26GTCAGAATAATGTCAAAGTGCTTACAGTGCAGGTAGTGAT 3204 mir-019b-2-prec 0.33GTGGCTGTGCAAATCCATGCAAAACTGATTGTGATAATGT 3205 mir-033-prec 0.3GTGGTGCATTGTAGTTGCATTGCATGTTCTGGTGGTACCC 3206 Hcd102 left 0.26ACTGGAATTATGTTTTATCTTAAGTCCACACTGGATCCTC 3207 MPR216 left 0.32GATCCTAGTAGTGCCAAAGTGCTCATAGTGCAGGTAGTTT 3208 Hcd975 left 0.25GGTTTTGTGTTTTTGTAAACAGCAGAAGGTATTAGTCCAT 3209 mir-019b-1-prec 0.3TTCTGCTGTGCAAATCCATGCAAAACTGACTGTGGTAGTG 3210 mir-135-2-prec 0.38CACTCTAGTGCTTTATGGCTTTTTATTCCTATGTGATAGT 3211 Hcd581 right 0.26AGGAGATATGCCAAGATATATTCACAGCTTTATATACACA 3212 Hcd536_HPR104 right 0.25GCTGCTCTGCTGAGGGGCTGGACTCTGTCCAGAAGCACCA 3213 mir-128b-precNo2 0.25GGGGGCCGATACACTGTACGAGAGTGAGTAGCAGGTCTCA 3214 HSTRNL 0.37TCCGGATGGAGCGTGGGTTCGAATCCCACTTCTGACACCA 3215 mir-025-prec 0.47ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 3216 mir-18bNo2 0.27AGCAGCTTAGAATCTACTGCCCTAAATGCCCCTTCTGGCA 3217 HPR262 left 0.26TCAGTTTGGTTCAGCTGGTATGCTTTCCAGTATCTCATTC 3218 Hcd923 right 0.33CTGGAGATAATGATTCTGCATTTCTAATTAACTCCCAGGT 3219 Hcd434 right 0.3CACTTTTTCCTTTGTGGAAATCCTGGGTGACATCACCTCC 3220 Hcd658 right 0.28GACTGCAGAGCAAAAGACACGATGGGTGTCTATTGTTTTC 3221 HPR129 left 0.29TTTTCCTGCTTGATTTGCTTAATGGAAGCTGACAGTGAAG 3222 mir-380-5p 0.32AGGTACCTGAAAAGATGGTTGACCATAGAACATGCGCTAT 3223 mir-093-prec-7.1 = 093-10.45 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 3224 mir-106-prec-X 0.5CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 3225 Hcd627 left 0.31GCATTAGGGAGAATAGTTGATGGATTACAAATCTCTGCAT 3226 mir-142-prec 0.33CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 3227 mir-018-prec 0.46TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC 3228 mir-020-prec 0.5TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG

TABLE 129 Teniposide microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3229 mir-124a-3-prec 0.25TTAAGGCACGCGGTGAATGCCAAGAGAGGCGCCTCCGCCG 3230 Hcd768 right 0.28GCCCTGGCGGAACGCTGAGAAGACAGTCGAACTTGACTAT 3231 HUMTRF 0.28GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 3232 mir-213-precNo1 0.25AACATTCATTGCTGTCGGTGGGTTGAACTGTGTGGACAAG 3233 mir-181b-precNo2 0.28ACCATCGACCGTTGATTGTACCCTATGGCTAACCATCATC 3234 Hcd783 left 0.28CAGGCTCACACCTCCCTCCCCCAACTCTCTGGAATGTATA 3235 mir-212-precNo2 0.32CGGACAGCGCGCCGGCACCTTGGCTCTAGACTGCTTACTG 3236 mir-124a-1-prec1 0.25ATACAATTAAGGCACGCGGTGAATGCCAAGAATGGGGCTG 3237 mir-342No1 0.29GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 3238 mir-142-prec 0.49CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 3239 HSHELA01 0.3GGCCGCAGCAACCTCGGTTCGTATCCGAGTCACGGCACCA 3240 mir-223-prec 0.27GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 3241 Hcd754 left 0.29TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC

TABLE 130 Dactinomycin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3242 mir-025-prec 0.27 ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG3243 mir-007-1-prec 0.28 TGTTGGCCTAGTTCTGTGTGGAAGACTAGTGATTTTGTTG 3244mir-093-prec-7.1 = 093-1 0.3 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT3245 Hcd794 right 0.33 GGCCACCACAGACACCAACAAGTTCAGTCCGTTTCTGCAG 3246mir-142-prec 0.34 CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG

TABLE 131 Tretinoin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3247 Hcd257 left 0.42 CTTCTTGTATAAGCACTGTGCTAAAATTGCAGACACTAGG3248 mir-148-prec 0.45 TGAGTATGATAGAAGTCAGTGCACTACAGAACTTTGTCTC 3249Hcd512 left 0.28 CTGCGCTCTCGGAAATGACTCGCTCCAATCCCGCTTCGCG 3250 HPR227right 0.25 CAGTGCAATGATATTGTCAAAGCATCTGGGACCAGCCTTG 3251 Hcd421 right0.37 AGTAAACAATGTCGGCTTTCCGCCTCCTCCCCTGCCATCC 3252 MPR203 left 0.39CTATATTGGACCGCAGCGCTGAGAGCTTTTGTGTTTAATG 3253 mir-017-precNo1 0.26GCATCTACTGCAGTGAAGGCACTTGTAGCATTATGGTGAC 3254 mir-219-2No1 0.26CTCAGGGGCTTCGCCACTGATTGTCCAAACGCAATTCTTG 3255 mir-328No1 0.3GAAAGTGCATACAGCCCCTGGCCCTCTCTGCCCTTCCGTC 3256 Hcd783 left 0.31CAGGCTCACACCTCCCTCCCCCAACTCTCTGGAATGTATA 3257 Hcd181 left 0.32TTGGCGTCCTTGTCTCTCTCTCCCCTGCCCAGTGGCCTCC 3258 HPR213 right 0.3AACAACTTTGTGCTGGTGCCGGGGAAGTTTGTGTCTCCAA 3259 mir-191-prec 0.31CAACGGAATCCCAAAAGCAGCTGTTGTCTCCAGAGCATTC 3260 mir-375 0.31TTTTGTTCGTTCGGCTCGCGTGAGGCAGGGGCGGCCTCTC 3261 mir-212-precNo2 0.26CGGACAGCGCGCCGGCACCTTGGCTCTAGACTGCTTACTG 3262 Hcd913 right 0.34CAAACATCATGTGACGTCTGTGGAGCGGCGGCGGCGGCGG 3263 Hcd716 right 0.48CAATAAATGTGCCTATAAAGGCGCCGGCTCCGGGGCGCGG 3264 MPR207 right 0.3AACAACTTTGTGCTGGTGCCGGGGAAGTTTGTGTCTCCTA 3265 HPR206 left 0.26CTATATTGGACCGCAGCGCTGAGAGCTTTTGTGTTTAATG 3266 mir-016b-chr3 0.29GTTCCACTCTAGCAGCACGTAAATATTGGCGTAGTGAAAT 3267 Hcd654 left 0.34AACGAGTAAAAGGCGTACATGGGAGCGCGGGGCGGCAGAG 3268 mir-195-prec 0.3TCTAGCAGCACAGAAATATTGGCACAGGGAAGCGAGTCTG 3269 Hcd425 left 0.25GGTTCTACTCTCTTACCCCTCCCCCACGTGGTTGTTGCTG 3270 mir-148aNo1 0.35TGAGTATGATAGAAGTCAGTGCACTACAGAACTTTGTCTC 3271 mir-142-prec 0.36CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 3272 mir-016a-chr13 0.25CAATGTCAGCAGTGCCTTAGCAGCACGTAAATATTGGCGT

TABLE 132 Ifosfamide microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3273 mir-092-prec-X = 092-2 0.28GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG 3274 mir-181b-2No1 0.28CTGATGGCTGCACTCAACATTCATTGCTGTCGGTGGGTTT 3275 Hcd417 right 0.28GGATTTAATGAGAAATATTGAGCCCTTTGGTTCAGGAACT 3276 Hcd440_HPR257 right 0.28GCTCTGTTGTGATAAATTGGCTGTGTGCTTCATTTGGACT 3277 mir-019b-2-prec 0.25GTGGCTGTGCAAATCCATGCAAAACTGATTGTGATAATGT 3278 mir-213-precNo1 0.39AACATTCATTGCTGTCGGTGGGTTGAACTGTGTGGACAAG 3279 mir-033-prec 0.29GTGGTGCATTGTAGTTGCATTGCATGTTCTGGTGGTACCC 3280 mir-092-prec-13 = 092-1No20.3 TCTGTATGGTATTGCACTTGTCCCGGCCTGTTGAGTTTGG 3281 mir-181b-precNo1 0.36TGAGGTTGCTTCAGTGAACATTCAACGCTGTCGGTGAGTT 3282 mir-128b-precNo1 0.46TCACAGTGAACCGGTCTCTTTCCCTACTGTGTCACACTCC 3283 mir-526a-2No2 0.29GAAAAGAACATGCATCCTTTCAGAGGGTTACTCTTTGAGA 3284 MPR95 left 0.25TTGTTGGACACTCTTTCCCTGTTGCACTACTGTGGGCCTC 3285 HPR220 right 0.27GAGCATCAGTATGTAGTGCAATCAGTCAGGAGAAAATGAG 3286 mir-133a-1 0.35CCTCTTCAATGGATTTGGTCCCCTTCAACCAGCTGTAGCT 3287 mir-148aNo1 0.3TGAGTATGATAGAAGTCAGTGCACTACAGAACTTTGTCTC 3288 mir-142-prec 0.4CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 3289 HPR169 right 0.26GTTTCTTTCTCACGGTAACTGGCAGCCTCGTTGTGGGCTG 3290 mir-223-prec 0.38GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 3291 mir-018-prec 0.27TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC 3292 mir-020-prec 0.25TAAAGTGCTTATAGTGCAGGTAGTGTTTAGTTATCTACTG 3293 mir-484 0.27GTCAGGCTCAGTCCCCTCCCGATAAACCCCTAAATAGGGA

TABLE 133 Tamoxifen microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3294 mir-092-prec-X = 092-2 0.31GTTCTATATAAAGTATTGCACTTGTCCCGGCCTGTGGAAG 3295 Hcd547 left 0.27AAAATCAGCTTTAATTAATTTGAGTGCCAGCTCTGTGTAT 3296 Hcd257 left 0.27CTTCTTGTATAAGCACTGTGCTAAAATTGCAGACACTAGG 3297 mir-148-prec 0.27TGAGTATGATAGAAGTCAGTGCACTACAGAACTTTGTCTC 3298 HUMTRS 0.25TCTAGCGACAGAGTGGTTCAATTCCACCTTTCGGGCGCCA 3299 mir-033-prec 0.27GTGGTGCATTGTAGTTGCATTGCATGTTCTGGTGGTACCC 3300 mir-092-prec-13 = 092-1No20.25 TCTGTATGGTATTGCACTTGTCCCGGCCTGTTGAGTTTGG 3301 mir-375 0.46TTTTGTTCGTTCGGCTCGCGTGAGGCAGGGGCGGCCTCTC 3302 mir-095-prec-4 0.28CGTTACATTCAACGGGTATTTATTGAGCACCCACTCTGTG 3303 mir-025-prec 0.35ACGCTGCCCTGGGCATTGCACTTGTCTCGGTCTGACAGTG 3304 mir-202-prec 0.34GATCTGGCCTAAAGAGGTATAGGGCATGGGAAGATGGAGC 3305 mir-007-1-prec 0.26TGTTGGCCTAGTTCTGTGTGGAAGACTAGTGATTTTGTTG 3306 mir-093-prec-7.1 = 093-10.44 CCAAAGTGCTGTTCGTGCAGGTAGTGTGATTACCCAACCT 3307 mir-106-prec-X 0.31CCTTGGCCATGTAAAAGTGCTTACAGTGCAGGTAGCTTTT 3308 mir-142-prec 0.25CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 3309 mir-223-prec 0.25GAGTGTCAGTTTGTCAAATACCCCAAGTGCGGCACATGCT 3310 mir-018-prec 0.26TAAGGTGCATCTAGTGCAGATAGTGAAGTAGATTAGCATC

TABLE 134 Floxuridine microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3311 HUMTRF 0.27 GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 3312HUMTRN 0.27 CAATCGGTTAGCGCGTTCGGCTGTTAACCGAAAGGTTGGT 3313mir-124a-1-prec1 0.31 ATACAATTAAGGCACGCGGTGAATGCCAAGAATGGGGCTG 3314mir-150-prec 0.33 CTCCCCATGGCCCTGTCTCCCAACCCTTGTACCAGTGCTG 3315 Hcd923left 0.26 TGGGAACCTTGTTAAAATGCAGATTCTGATTCTCAGGTCT 3316 HPR181 left 0.28GAAGAAACATCTCAAATCATGCTGACAGCATTTTCACTAT 3317 Hcd569 right 0.26TTATTGCTTGAATGAGTTTCAGGGTATTGGCCTTCATAAA 3318 mir-199a-2-prec 0.25TCGCCCCAGTGTTCAGACTACCTGTTCAGGACAATGCCGT 3319 Hcd754 left 0.28TCCTCCTCCTCCTTTTCGTTCCGGCTCCCTGGCTGGCTCC 3320 mir-4323p 0.3CCTTACGTGGGCCACTGGATGGCTCCTCCATGTCTTGGAG

TABLE 135 Irinotecan microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3321 HUMTRF 0.27 GATCTAAAGGTCCCTGGTTCGATCCCGGGTTTCGGCACCA 3322mir-380-5p 0.27 AGGTACCTGAAAAGATGGTTGACCATAGAACATGCGCTAT 3323 mir-342No10.25 GTCTCACACAGAAATCGCACCCGTCACCTTGGCCTACTTA 3324 mir-142-prec 0.35CCCATAAAGTAGAAAGCACTACTAACAGCACTGGAGGGTG 3325 Hcd200 right 0.25CAATTAGCCAATTGTGGGTATAATTAGCTGCATGTAGAAT

TABLE 136 Satraplatin microRNA biomarkers. SEQ ID NO Medianprobe CorrSequence 3326 Hcd289 left 0.31 TTCCTCTCAGAGCATGTTGTCATAGAAGTAAATGAAAAGG3327 Hcd939 right 0.25 CTCTCCTGCACATAATGAGGTCTGATTTACTGTGATCATT 3328Hcd330 right 0.28 ATTAATGGTAATTATGTGCGTAAATCCCCATGCTCTCAAT 3329 HPR76right 0.25 GAGCCGTTTAAATTTAGCGCTTTGGGCTGCCTGGAGCGAG 3330 Hcd111 left0.29 GCAGGGGATTTGAGGGGTGGTTGTGTGATTTGTACAGCTG 3331 Hcd976 right 0.36CTTCTCAGAGTTGGAGATGAAAGAAAGAGAAGGTGGCCAC 3332 mir-15aNo1 0.29CCTTGGAGTAAAGTAGCAGCACATAATGGTTTGTGGATTT 3333 mir-001b-1-prec1 0.26AATGCTATGGAATGTAAAGAAGTATGTATTTTTGGTAGGC 3334 mir-450-1 0.36AACGATACTAAACTGTTTTTGCGATGTGTTCCTAATATGC 3335 mir-200bNo2 0.3CCAGCTCGGGCAGCCGTGGCCATCTTACTGGGCAGCATTG 3336 Hcd578 right 0.3AATGATTGTAGAGGGGCGGGGCATGAAGAGTGCCGTTCTG 3337 mir-200a-prec 0.28GTCTCTAATACTGCCTGGTAATGATGACGGCGGAGCCCTG

1. A method of determining sensitivity of a cancer patient to atreatment for cancer comprising measuring a level of expression of atleast one gene in a cell of said patient, said gene selected from thegroup consisting of ACTB, ACTN4, ADA, ADAM9, ADAMTS1, ADD1, AF1Q, AIF1,AKAP1, AKAP13, AKR1C1, AKT1, ALDH2, ALDOC, ALG5, ALMS1, ALOX15B, AMIGO2,AMPD2, AMPD3, ANAPC5, ANP32A, ANP32B, ANXA1, AP1G2, APOBEC3B, APRT,ARHE, ARHGAP15, ARHGAP25, ARHGDIB, ARHGEF6, ARL7, ASAH1, ASPH, ATF3,ATIC, ATP2A2, ATP2A3, ATP5D, ATP5G2, ATP6V1B2, BC008967, BCAT1, BCHE,BCL11B, BDNF, BHLHB2, BIN2, BLMH, BMI1, BNIP3, BRDT, BRRN1, BTN3A3,C11orf2, C14orf139, C15orf25, C18orf10, C1orf24, C1orf29, C1orf18,C1QR1, C22orf18, C6 orf2, CACNA1G, CACNB3, CALM1, CALML4, CALU, CAP350,CASP2, CASP6, CASP7, CAST, CBLB, CCNA2, CCNB1IP1, CCND3, CCR7, CCR9,CD1A, CD1C, CD1D, CD1E, CD2, CD28, CD3D, CD3E, CD3G, CD3Z, CD44, CD47,CD59, CD6, CD63, CD8A, CD8B1, CD99, CDC10, CDCl₄B, CDH11, CDH2, CDKL5,CDKN2A, CDW52, CECR1, CENPB, CENTB1, CENTG2, CEP1, CG018, CHRNA3, CHS1,CIAPIN1, CKAP4, CKIP-1, CNP, COL4A1, COL5A2, COL6A1, CORO1C, CRABP1,CRK, CRY1, CSDA, CTBP1, CTSC, CTSL, CUGBP2, CUTC, CXCL1, CXCR4, CXorf9,CYFIP2, CYLD, CYR61, DATF1, DAZAP1, DBN1, DBT, DCTN1, DDX18, DDX5, DGKA,DIAPH1, DKC1, DKFZP434J154, DKFZP564C186, DKFZP564G2022, DKFZp564J157,DKFZP564K0822, DNAJC10, DNAJC7, DNAPTP6, DOCK10, DOCK2, DPAGT1, DPEP2,DPYSL3, DSIPI, DUSP1, DXS9879E, EEF1B2, EFNB2, EHD2, EIF5A, ELK3, ENO2,EPAS1, EPB41L4B, ERCC2, ERG, ERP70, EVER1, EVI2A, EVL, EXT1, EZH2, F2R,FABP5, FAD104, FAM46A, FAU, FCGR2A, FCGR2C, FER1L3, FHL1, FHOD1, FKBP1A,FKBP9, FLJ10350, FLJ10539, FLJ10774, FLJ12270, FLJ13373, FLJ20859,FLJ21159, FLJ22457, FLJ35036, FLJ46603, FLNC, FLOT1, FMNL1, FNBP1,FOLH1, FOXF2, FSCN1, FTL, FYB, FYN, GOS2, G6PD, GALIG, GALNT6, GATA2,GATA3, GFPT1, GIMAP5, GIT2, GJA1, GLRB, GLTSCR2, GLUL, GMDS, GNAQ, GNB2,GNB5, GOT2, GPR65, GPRASP1, GPSM3, GRP58, GSTM2, GTF3A, GTSE1, GZMA,GZMB, H1F0, H1FX, H2AFX, H3F3A, HA-1, HEXB, HIC, HIST1H4C, HK1, HLA-A,HLA-B, HLA-DRA, HMGA1, HMGN2, HMMR, HNRPA1, HNRPD, HNRPM, HOXA9,HRMT1L1, HSA9761, HSPA5, HSU79274, HTATSF1, ICAM1, ICAM2, IER3, IFI16,IFI44, IFITM2, IFITM3, IFRG28, IGFBP2, IGSF4, IL13RA2, IL21R, IL2RG,IL4R, IL6, IL6R, IL6ST, IL8, IMPDH2, INPP5D, INSIG1, IQGAP1, IQGAP2,IRS2, ITGA5, ITM2A, JARID2, JUNB, K-ALPHA-1, KHDRBS1, KIAA0355,KIAA0802, KIAA0877, KIAA0922, KIAA1078, KIAA1128, KIAA1393, KIFC1,LAIR1, LAMB1, LAMB3, LAT, LBR, LCK, LCP1, LCP2, LEF1, LEPRE1, LGALS1,LGALS9, LHFPL2, LNK, LOC54103, LOC55831, LOC81558, LOC94105, LONP, LOX,LOXL2, LPHN2, LPXN, LRMP, LRP12, LRRC5, LRRN3, LST1, LTB, LUM, LY9,LY96, MAGEB2, MAL, MAP1B, MAP1LC3B, MAP4K1, MAPK1, MARCKS, MAZ, MCAM,MCL1, MCM5, MCM7, MDH2, MDN1, MEF2C, MFNG, MGC17330, MGC21654, MGC2744,MGC4083, MGC8721, MGC8902, MGLL, MLPH, MPHOSPH6, MPP1, MPZL1, MRP63,MRPS2, MT1E, MT1K, MUF1, MVP, MYB, MYL9, MYO1B, NAP1L1, NAP1L2, NARF,NASP, NCOR2, NDN, NDUFAB1, NDUFS6, NFKBIA, NID2, NIPA2, NME4, NME7,NNMT, NOL5A, NOL8, NOMO2, NOTCH1, NPC1, NQO1, NR1D2, NUDC, NUP210,NUP88, NVL, NXF1, OBFC1, OCRL, OGT, OXA1L, P2RX5, P4HA1, PACAP, PAF53,PAFAH1B3, PALM2-AKAP2, PAX6, PCBP2, PCCB, PFDN5, PFN1, PFN2, PGAM1,PHEMX, PHLDA1, PIM2, PITPNC1, PLAC8, PLAGL1, PLAUR, PLCB1, PLEK2,PLEKHC1, PLOD2, PLSCR1, PNAS-4, PNMA2, POLR2F, PPAP2B, PRF1, PRG1,PRIM1, PRKCH, PRKCQ, PRKD2, PRNP, PRP19, PRPF8, PRSS23, PSCDBP, PSMB9,PSMC3, PSME2, PTGER4, PTGES2, PTOV1, PTP4A3, PTPN7, PTPNS1, PTRF, PURA,PWP1, PYGL, QKI, RAB3GAP, RAB7L1, RAB9P40, RAC2, RAFTLIN, RAG2, RAP1B,RASGRP2, RBPMS, RCN1, RFC3, RFC5, RGC32, RGS3, RHOH, RIMS3, RIOK3,RIPK2, RIS1, RNASE6, RNF144, RPL10, RPL10A, RPL12, RPL13A, RPL17, RPL18,RPL36A, RPLP0, RPLP2, RPS15, RPS19, RPS2, RPS4X, RPS4Y1, RRAS, RRAS2,RRBP1, RRM2, RUNX1, RUNX3, S100A4, SART3, SATB1, SCAP1, SCARB1, SCN3A,SEC31L2, SEC61G, SELL, SELPLG, SEMA4G, SEPT10, SEPT6, SERPINA1,SERPINB1, SERPINB6, SFRS5, SFRS6, SFRS7, SH2D1A, SH3GL3, SH3TC1, SHD1,SHMT2, SIAT1, SKB1, SKP2, SLA, SLC1A4, SLC20A1, SLC25A15, SLC25A5,SLC39A14, SLC39A6, SLC43A3, SLC4A2, SLC7A11, SLC7A6, SMAD3, SMOX, SNRPA,SNRPB, SOD2, SOX4, SP140, SPANXC, SPI1, SRF, SRM, SSA2, SSBP2, SSRP1,SSSCA1, STAG3, STAT1, STAT4, STAT5A, STC1, STC2, STOML2, T3JAM, TACC1,TACC3, TAF5, TAL1, TAP1, TARP, TBCA, TCF12, TCF4, TFDP2, TFPI, TIMM17A,TIMP1, TJP1, TK2, TM4SF1, TM4SF2, TM4SF8, TM6SF1, TMEM2, TMEM22, TMSB10,TMSNB, TNFAIP3, TNFAIP8, TNFRSF10B, TNFRSF1A, TNFRSF7, TNIK, TNPO1,TOB1, TOMM20, TOX, TPK1, TPM2, TRA@, TRA1, TRAM2, TRB@, TRD@, TRIM,TRIM14, TRIM22, TRIM28, TRIP13, TRPV2, TUBGCP3, TUSC3, TXN, TXNDC5,UBASH3A, UBE2A, UBE2L6, UBE2S, UCHL1, UCK2, UCP2, UFD1L, UGDH, ULK2,UMPS, UNG, USP34, USP4, VASP, VAV1, VLDLR, VWF, WASPIP, WBSCR20A,WBSCR20C, WHSC1, WNT5A, ZAP70, ZFP36L1, ZNF32, ZNF335, ZNF593, ZNFN1A1,and ZYX, wherein said level of expression of said gene indicates saidcell is sensitive to said treatment.
 2. The method of claim 1, whereinsaid at least one gene is selected from the group consisting of RPS4X,S100A4, NDUFS6, C14orf139, SLC25A5, RPL10, RPL12, EIF5A, RPL36A, BLMH,CTBP1, TBCA, MDH2, and DXS9879E, or wherein the method further comprisesmeasuring a level of expression of at least one gene selected from thegroup consisting of UBB, B2M, MAN1A1, and SUI1, or wherein the methodfurther comprises measuring a level of at least one microRNA selectedfrom the group consisting of Hcd892, Hcd678, hsa-mir-007-1-prec, MPR243,Hcd654, hsa-mir-487, Hcd794, Hcd739, and Hcd562, wherein said level ofexpression of said gene or said level of said microRNA indicates thatsaid cell is sensitive to Vincristine.
 3. The method of claim 1, whereinsaid at least one gene is selected from the group consisting of C1 QR1,SLA, PTPN7, ZNFN1A1, CENTB1, IFI16, ARHGEF6, SEC31L2, CD3Z, GZMB, CD3D,MAP4K1, GPR65, PRF1, ARHGAP15, TM6SF1, and TCF4, or wherein the methodfurther comprises measuring a level of expression of at least one geneselected from the group consisting of HCLS1, CD53, PTPRCAP, and PTPRC,or wherein the method further comprises measuring a level of expressionof at least one microRNA selected from the group consisting of HUMTRF,HPR187, hsa-mir-450-1, hsa-mir-155-prec, hsa-mir-515-15p,hsa-mir-181b-prec, hsa-mir-124a-1-prec1, hsa-mir-450-2, Hcd923,hsa-mir-342, hsa-mir-142-prec, hsa-mir-223-prec, Hcd754, andHcd213_HPR182, wherein said level of expression of said gene or microRNAindicates that said cell is sensitive to Cisplatin.
 4. The method ofclaim 1, wherein said at least one gene is selected from the groupconsisting of SRM, SCARB1, SIAT1, CUGBP2, ICAM1, WASPIP, ITM2A,PALM2-AKAP2, PTPNS1, MPP1, LNK, FCGR2A, RUNX3, EVI2A, BTN3A3, LCP2,BCHE, LY96, LCP1, IFI16, MCAM, MEF2C, SLC1A4, FYN, C1orf38, CHS1,FCGR2C, TNIK, AMPD2, SEPT6, RAFTLIN, SLC43A3, RAC2, LPXN, CKIP-1,FLJ10539, FLJ35036, DOCK10, TRPV2, IFRG28, LEF1, and ADAMTS1, or whereinthe method further comprises measuring a level of expression of at leastone gene selected from the group consisting of MSN, SPARC, VIM, GAS7,ANPEP, EMP3, BTN3A2, FN1, and CAPN3, or wherein the method furthercomprises measuring a level of expression of at least one microRNAselected from the group consisting of MPR121, HUMTRS, hsa-mir-2,3-prec,hsa-mir-155-prec, hsa-mir-147-prec, hsa-mir-100, hsa-mir-138-1-prec,hsa-mir-140, hsa-mir-146-prec, hsa-mir-509, hsa-mir-146b, Hcd514,Hcd397, Hcd731, hsa-mir-034-prec, and hsa-mir-100-1/2-prec, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to Azaguanine.
 5. The method of claim 1, wherein said at leastone gene is selected from the group consisting of CD99, INSIG1, PRG1,MUF1, SLA, SSBP2, GNB5, MFNG, PSMB9, EVI2A, PTPN7, PTGER4, CXorf9,ZNFN1A1, CENTB1, NAP1L1, HLA-DRA, IFI16, ARHGEF6, PSCDBP, SELPLG, LAT,SEC31L2, CD3Z, SH2D1A, GZMB, SCN3A, RAFTLIN, DOCK2, CD3D, RAC2, ZAP70,GPR65, PRF1, ARHGAP15, NOTCH1, and UBASH3A, or wherein the methodfurther comprises measuring a level of expression of at least one geneselected from the group consisting of LAPTM5, HCLS1, CD53, GMFG,PTPRCAP, PTPRC, CORO1A, and ITK, or wherein the method further comprisesmeasuring a level of expression of at least one microRNA selected fromthe group consisting of Hcd415, Hcd768, HUMTRF, Hcd866, Hcd145, HUMTRAB,Hcd913, HPR163, Hcd697, Hcd755, Hcd716, MPR207, HSTRNL, HPR206, MPR243,Hcd654, MPR130, Hcd782, Hcd794, Hcd739, hsa-mir-142-prec, HSHELA01,HUMTRV1A, and Hcd754, wherein said level of expression of said gene ormicroRNA indicates that said cell is sensitive to Etoposide.
 6. Themethod of claim 1, wherein said at least one gene is selected from thegroup consisting of CD99, ALDOC, SLA, SSBP2, IL2RG, CXorf9, RHOH,ZNFN1A1, CENTB1, CD1C, MAP4K1, CD3G, CCR9, CXCR4, ARHGEF6, SELPLG, LAT,SEC31L2, CD3Z, SH2D1A, CD1A, LAIR1, TRB@, CD3D, WBSCR20C, ZAP70, IFI44,GPR65, AIF1, ARHGAP15, NARF, and PACAP, or wherein the method furthercomprises measuring a level of expression of at least one gene selectedfrom the group consisting of LAPTM5, HCLS1, CD53, GMFG, PTPRCAP, TCF7,CD1B, PTPRC, CORO1A, HEM1, and ITK, or wherein the method furthercomprises measuring a level of expression of at least one microRNAselected from the group consisting of Hcd768, hsa-mir-483, Hcd145,hsa-mir-197-prec, hsa-mir-2,2-prec, HPR163, Hcd654, hsa-mir-342, Hcd794,hsa-mir-142-prec, and Hcd754, wherein said level of expression of saidgene or microRNA indicates that said cell is sensitive to Adriamycin. 7.The method of claim 1, wherein said at least one gene is selected fromthe group consisting of RPL12, RPLP2, MYB, ZNFN1A1, SCAP1, STAT4, SP140,AMPD3, TNFAIP8, DDX18, TAF5, RPS2, DOCK2, GPR65, HOXA9, FLJ12270, andHNRPD, or wherein the method further comprises measuring a level ofexpression of at least one gene selected from the group consisting ofRPL32, FBL, and PTPRC, or wherein the method further comprises measuringa level of expression of at least one microRNA selected from the groupconsisting of hsa-mir-092-prec-X=092-2, hsa-mir-096-prec-7, Hcd605,hsa-mir-007-2-prec, hsa-mir-019b-2-prec, MPR216, hsa-mir-019b-1-prec,hsa-mir-135-2-prec, HSTRNL, hsa-mir-025-prec, hsa-mir-007-1-prec,hsa-mir-019a-prec, hsa-mir-380-5p, hsa-mir-093-prec-7.1=093-1,hsa-mir-106-prec-X, hsa-mir-142-prec, hsa-mir-018-prec, andhsa-mir-020-prec, wherein said level of expression of said gene ormicroRNA indicates that said cell is sensitive to Aclarubicin.
 8. Themethod of claim 1, wherein said at least one gene is selected from thegroup consisting of PGAM1, DPYSL3, INSIG1, GJA1, BNIP3, PRG1, G6PD,PLOD2, LOXL2, SSBP2, C1orf29, TOX, STC1, TNFRSF1A, NCOR2, NAP1L1,LOC94105, ARHGEF6, GATA3, TFPI, LAT, CD3Z, AF1Q, MAP1B, TRIM22, CD3D,BCAT1, IFI44, CUTC, NAP1L2, NME7, FLJ21159, and COL5A2, or wherein themethod further comprises measuring a level of expression of at least onegene selected from the group consisting of BASP1, COL6A2, PTPRC, PRKCA,CCL2, and RAB31, or wherein the method further comprises measuring alevel of expression of at least one microRNA selected from the groupconsisting of Hcd768, HUMTRF, hsa-mir-2,3-prec, hsa-mir-181b-prec,MPR244, hsa-mir-409-3p, HSTRNL, hsa-mir-382, hsa-mir-342,hsa-mir-142-prec, and Hcd200, wherein said level of expression of saidgene or microRNA indicates that said cell is sensitive to Mitoxantrone.9. The method of claim 1, wherein said at least one gene is selectedfrom the group consisting of STC1, GPR65, DOCK10, COL5A2, FAM46A, andLOC54103, or wherein the method further comprises measuring a level ofexpression of at least one microRNA selected from the group consistingof HUMTRF, Hcd148_HPR225left, Hcd938, MPR174, and hsa-mir-4323p, whereinsaid level of expression of said gene or microRNA indicates that saidcell is sensitive to Mitomycin.
 10. The method of claim 1, wherein saidat least one gene is selected from the group consisting of RPL10, RPS4X,NUDC, DKC1, DKFZP564C186, PRP19, RAB9P40, HSA9761, GMDS, CEP1, IL13RA2,MAGEB2, HMGN2, ALMS1, GPR65, FLJ10774, NOL8, DAZAP1, SLC25A15, PAF53,DXS9879E, PITPNC1, SPANXC, and KIAA1393, or wherein the method furthercomprises measuring a level of expression of RALY, or wherein the methodfurther comprises measuring a level of expression of at least onemicroRNA selected from the group consisting of hsa-mir-092-prec-X=092-2,hsa-mir-096-prec-7, hsa-mir-101-prec-9, hsa-mir-20b,hsa-mir-019b-2-prec, hsa-mir-032-prec, MPR156, hsa-mir-019b-1-prec,hsa-mir-135-2-prec, hsa-mir-025-prec, hsa-mir-007-1-prec, hsa-mir-361,hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X, hsa-mir-098-prec-X,hsa-mir-142-prec, HPR169, hsa-mir-018-prec, and hsa-mir-020-prec,wherein said level of expression of said gene or microRNA indicates thatsaid cell is sensitive to Paclitaxel.
 11. The method of claim 1, whereinsaid at least one gene is selected from the group consisting of PFN1,PGAM1, K-ALPHA-1, CSDA, UCHL1, PWP1, PALM2-AKAP2, TNFRSF1A, ATP5G2,AF1Q, NME4, and FHOD1, or wherein the method further comprises measuringa level of expression of at least one microRNA selected from the groupconsisting of hsa-mir-123-prec, Hcd257, hsa-mir-155-prec, ath-MIR180a,Hcd448, HSTRNL, MPR174, Hcd200, hsa-mir-4323p, and HPR244, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to Gemcitabine.
 12. The method of claim 1, wherein said atleast one gene is selected from the group consisting of ANP32B, GTF3A,RRM2, TRIM14, SKP2, TRIP13, RFC3, CASP7, TXN, MCM5, PTGES2, OBFC1,EPB41L4B, and CALML4, or wherein the method further comprises measuringa level of expression of at least one microRNA selected from the groupconsisting of hsa-mir-096-prec-7, hsa-mir-095-prec-4, HSTRNL, andhsa-mir-007-1-prec, wherein said level of expression of said gene ormicroRNA indicates that said cell is sensitive to Taxotere.
 13. Themethod of claim 1, wherein said at least one gene is selected from thegroup consisting of IFITM2, UBE2L6, USP4, ITM2A, IL2RG, GPRASP1, PTPN7,CXorf9, RHOH, GIT2, ZNFN1A1, CEP1, TNFRSF7, MAP4K1, CCR7, CD3G, ATP2A3,UCP2, GATA3, CDKN2A, TARP, LAIR1, SH2D1A, SEPT6, HA-1, ERCC2, CD3D,LST1, AIF1, ADA, DATF1, ARHGAP15, PLAC8, CECR1, LOC81558, and EHD2, orwherein the method further comprises measuring a level of expression ofat least one gene selected from the group consisting of LAPTM5, ITGB2,ANPEP, CD53, CD37, ADORA2A, GNA15, PTPRC, CORO1A, HEM1, FLII, andCREB3L1, or wherein the method further comprises measuring a level ofexpression of at least one microRNA selected from the group consistingof MPR141, hsa-mir-424, Hcd690, Hcd783, hsa-mir-150-prec, Hcd266,hsa-mir-503, hsa-mir-128b-prec, Hcd397, and hsa-mir-484, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to Dexamethasone.
 14. The method of claim 1, wherein said atleast one gene is selected from the group consisting of ITM2A, RHOH,PRIM1, CENTB1, NAP1L1, ATP5G2, GATA3, PRKCQ, SH2D1A, SEPT6, NME4, CD3D,CD1E, ADA, and FHOD1, or wherein the method further comprises measuringa level of expression of at least one gene selected from the groupconsisting of GNA15, PTPRC, and RPL13, or wherein the method furthercomprises measuring a level of expression of at least one microRNAselected from the group consisting of HUMTRF, hsa-mir-155-prec,hsa-mir-515-15p, Hcd938, Hcd642, Hcd120, hsa-mir-380-5p, hsa-mir-342,hsa-mir-142-prec, hsa-mir-223-prec, and hsa-mir-4323p, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to Ara-C.
 15. The method of claim 1, wherein said at least onegene is selected from the group consisting of CD99, ARHGDIB, VWF, ITM2A,LGALS9, INPP5D, SATB1, TFDP2, SLA, IL2RG, MFNG, SELL, CDW52, LRMP,ICAM2, RIMS3, PTPN7, ARHGAP25, LCK, CXorf9, RHOH, GIT2, ZNFN1A1, CENTB1,LCP2, SPI1, GZMA, CEP1, CD8A, SCAP1, CD2, CD1C, TNFRSF7, VAV1, MAP4K1,CCR7, C6orf32, ALOX1SB, BRDT, CD3G, LTB, ATP2A3, NVL, RASGRP2, LCP1,CXCR4, PRKD2, GATA3, TRA@, KIAA0922, TARP, SEC31L2, PRKCQ, SH2D1A,CHRNA3, CD1A, LST1, LAIR1, CACNA1G, TRB@, SEPT6, HA-1, DOCK2, CD3D,TRD@, T3JAM, FNBP1, CD6, AIF1, FOLH1, CD1E, LY9, ADA, CDKL5, TRIM, EVL,DATF1, RGC32, PRKCH, ARHGAP15, NOTCH1, BIN2, SEMA4G, DPEP2, CECR1,BCL11B, STAG3, GALNT6, UBASH3A, PHEMX, FLJ13373, LEF1, IL21R, MGC17330,AKAP13, ZNF335, and GIMAP5, or wherein the method further comprisesmeasuring a level of expression of at least one gene selected from thegroup consisting of SRRM1, LAPTM5, ITGB2, CD53, CD37, GMFG, PTPRCAP,GNA15, BLM, PTPRC, CORO1A, PRKCB1, HEM1, and UGT2B17, or wherein themethod further comprises measuring a level of expression of at least onemicroRNA selected from the group consisting of Hcd544,hsa-mir-181c-prec, Hcd517, MPR151, hsa-mir-2,3-prec, hsa-mir-181b-prec,hsa-mir-150-prec, hsa-mir-153-1-prec1, hsa-mir-128 b-prec, Hcd812,hsa-mir-195-prec, hsa-mir-342, hsa-mir-370, hsa-mir-142-prec,hsa-mir-223-prec, and hsa-mir-484, wherein said level of expression ofsaid gene or microRNA indicates that said cell is sensitive toMethylprednisolone.
 16. The method of claim 1, wherein said at least onegene is selected from the group consisting of PRPF8, RPL18, GOT2,RPL13A, RPS15, RPLP2, CSDA, KHDRBS1, SNRPA, IMPDH2, RPS19, NUP88, ATP5D,PCBP2, ZNF593, HSU79274, PRIM1, PFDN5, OXA1L, H3F3A, ATIC, CIAPIN1,RPS2, PCCB, SHMT2, RPLP0, HNRPA1, STOML2, SKB1, GLTSCR2, CCNB1IP1,MRPS2, FLJ20859, and FLJ12270, or wherein the method further comprisesmeasuring a level of expression of at least one gene selected from thegroup consisting of RNPS1, RPL32, EEF1G, PTMA, RPL13, FBL, RBMX, andRPS9, or wherein the method further comprises measuring a level ofexpression of at least one microRNA selected from the group consistingof hsa-mir-092-prec-X=092-2, hsa-mir-096-prec-7, hsa-mir-123-prec,Hcd250, hsa-mir-518e, HPR232, Hcd263, hsa-mir-516-33p, Hcd605, Hcd373,MPR254, MPR215, HUMTRF, hsa-mir-106a, hsa-mir-20b, Hcd361, Hcd412,Hcd781, hsa-mir-019b-2-prec, HPR214, Hcd807, Hcd817, Hcd788, Hcd970,Hcd148_HPR225left, Hcd102, Hcd246, HPR199, HPR233, Hcd383, MPR224,HPR172, MPR216, hsa-mir-321, Hcd586, Hcd587, Hcd249, Hcd279, HPR159,Hcd689, Hcd691, hsa-mir-019b-1-prec, Hcd413, Hcd581, Hcd536_HPR104,Hcd230, HPR154, Hcd270, Hcd649, Hcd889, Hcd938, HPR266,hsa-mir-025-prec, Hcd355_HPR190, MPR162, Hcd923, MPR237, MPR174,hsa-mir-019a-prec, hsa_mir_(—)490_Hcd20, hsa-mir-380-5p,hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X, Hcd627,hsa-mir-142-prec, HPR169, hsa-mir-001b-2-prec, hsa-mir-018-prec,hsa-mir-020-prec, Hcd404, hsa-mir-384, and hsa-mir-4323p, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to Methotrexate.
 17. The method of claim 1, wherein said atleast one gene is selected from the group consisting of PFN1, HK1, MCL1,ZYX, RAP1B, GNB2, EPAS1, PGAM1, CKAP4, DUSP1, MYL9, K-ALPHA-1, LGALS1,CSDA, IFITM2, ITGA5, DPYSL3, JUNB, NFKBIA, LAMB1, FHL1, INSIG1, TIMP1,GJA1, PSME2, PRG1, EXT1, DKFZP434J154, MVP, VASP, ARL7, NNMT, TAP1,PLOD2, ATF3, PALM2-AKAP2, IL8, LOXL2, IL4R, DGKA, STC2, SEC61G, RGS3,F2R, TPM2, PSMB9, LOX, STC1, PTGER4, IL6, SMAD3, WNT5A, BDNF, TNFRSF1A,FLNC, DKFZP564K0822, FLOT1, PTRF, HLA-B, MGC4083, TNFRSF10B, PLAGL1,PNMA2, TFPI, LAT, GZMB, CYR61, PLAUR, FSCN1, ERP70, AF1Q, HIC, COL6 μl,IFITM3, MAP1B, FLJ46603, RAFTLIN, RRAS, FTL, KIAA0877, MT1E, CDC10,DOCK2, TRIM22, RIS1, BCAT1, PRF1, DBN1, MT1K, TMSB10, FLJ10350, C1orf24,NME7, TMEM22, TPK1, COL5A2, ELK3, CYLD, ADAMTS1, EHD2, and ACTB, orwherein the method further comprises measuring a level of expression ofat least one gene selected from the group consisting of MSN, ACTR2,AKR1B1, VIM, ITGA3, OPTN, M6PRBP1, COL1A1, BASP1, ANPEP, TGFB1, NFIL3,NK4, CSPG2, PLAU, COL6A2, UBC, FGFR1, BAX, COL4A2, and RAB31, or whereinthe method further comprises measuring a level of expression of at leastone microRNA selected from the group consisting of hsa-mir-376a,hsa-mir-155-prec, hsa-mir-409-3p, hsa-mir-495, Hcd498,hsa-mir-199a-2-prec, hsa-mir-382, HPR271, hsa-mir-145-prec, andhsa-mir-199a-1-prec, wherein said level of expression of said gene ormicroRNA indicates that said cell is sensitive to Bleomycin.
 18. Themethod of claim 1, wherein said at least one gene is selected from thegroup consisting of SSRP1, NUDC, CTSC, AP1G2, PSME2, LBR, EFNB2,SERPINA1, SSSCA1, EZH2, MYB, PRIM1, H2AFX, HMGA1, HMMR, TK2, WHSC1,DIAPH1, LAMB3, DPAGT1, UCK2, SERPINB1, MDN1, BRRN1, GOS2, RAC2,MGC21654, GTSE1, TACC3, PLEK2, PLAC8, HNRPD, and PNAS-4, or wherein themethod further comprises measuring the level of expression of PTMA, orwherein the method further comprises measuring a level of expression ofat least one microRNA selected from the group consisting ofhsa-mir-092-prec-X=092-2, hsa-mir-101-prec-9, hsa-mir-144-prec,hsa-mir-519a-1, hsa-mir-519b, hsa-mir-015b-prec, hsa-mir-106a,hsa-mir-16-1, hsa-mir-181d, hsa-mir-017-prec, hsa-mir-019b-2-prec,hsa-mir-192, hsa-mir-2,3-prec, hsa-mir-2,5-prec, hsa-mir-107,hsa-mir-200b, hsa-mir-103-prec-5=103-1, hsa-mir-519a-1/526c, MPR216,hsa-mir-019b-1-prec, hsa-mir-107-prec-10, hsa-mir-135-2-prec,hsa-mir-103-2-prec, hsa-mir-519a-2, hsa-mir-025-prec, hsa-mir-16-2,MPR95, hsa-mir-016b-chr3, Hcd948, hsa-mir-195-prec,hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X, hsa-mir-142-prec,hsa-mir-519c/526c, hsa-mir-200a-prec, hsa-mir-016a-chr13,hsa-mir-018-prec, and hsa-mir-020-prec, wherein said level of expressionof said gene or microRNA indicates that said cell is sensitive toMethyl-GAG.
 19. The method of claim 1, wherein said at least one gene isselected from the group consisting of ITGA5, TNFAIP3, WNT5A, FOXF2,LOC94105, IFI16, LRRN3, DOCK10, LEPRE1, COL5A2, and ADAMTS1, or whereinthe method further comprises measuring a level of expression of at leastone gene selected from the group consisting of MSN, VIM, CSPG2, andFGFR1, or wherein the method further comprises measuring a level ofexpression of at least one microRNA selected from the group consistingof Hcd829, HUMTRF, HPR187, Hcd210_HPR205, hsa-mir-379, hsa-mir-2,3-prec,hsa-mir-4325p, hsa-mir-450-1, hsa-mir-155-prec, Hcd28_HPR39right,MPR244, hsa-mir-409-3p, hsa-mir-124a-1-prec1, hsa-mir-154-prec1,hsa-mir-495, hsa-mir-515-23p, Hcd438right, Hcd770, hsa-mir-382,hsa-mir-223-prec, Hcd754, and Hcd213_HPR182, wherein said level ofexpression of said gene or microRNA indicates that said cell issensitive to Carboplatin.
 20. The method of claim 1, wherein said atleast one gene is selected from the group consisting of RPL18, RPL10A,ANAPC5, EEF1B2, RPL13A, RPS15, AKAP1, NDUFAB1, APRT, ZNF593, MRP63,IL6R, SART3, UCK2, RPL17, RPS2, PCCB, TOMM20, SHMT2, RPLP0, GTF3A,STOML2, DKFZp564J157, MRPS2, ALG5, and CALML4, or wherein the methodfurther comprises measuring a level of expression of at least one geneselected from the group consisting of RNPS1, RPL13, RPS6, and RPL3, orwherein the method further comprises measuring a level of expression ofat least one microRNA selected from the group consisting ofhsa-mir-096-prec-7, hsa-mir-429, Hcd693, HPR214, Hcd586, Hcd249, Hcd689,hsa-mir-194-2, Hcd581, Hcd270, hsa-mir-025-prec, Hcd340,hsa-mir-007-1-prec, hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X,Hcd794, hsa-mir-020-prec, and hsa-mir-4323p, wherein said level ofexpression of said gene or microRNA indicates that said cell issensitive to 5-FU (5-Fluorouracil).
 21. The method of claim 1, whereinsaid at least one gene is selected from the group consisting of KIFC1,VLDLR, RUNX1, PAFAH1B3, H1FX, RNF144, TMSNB, CRY1, MAZ, SLA, SRF, UMPS,CD3Z, PRKCQ, HNRPM, ZAP70, ADD1, RFC5, TM4SF2, PFN2, BMI1, TUBGCP3,ATP6V1B2, CD1D, ADA, CD99, CD2, CNP, ERG, CD3E, CD1A, PSMC3, RPS4Y1,AKT1, TAL1, UBE2A, TCF12, UBE2S, CCND3, PAX6, RAG2, GSTM2, SATB1, NASP,IGFBP2, CDH2, CRABP1, DBN1, AKR1C1, CACNB3, CASP2, CASP2, LCP2, CASP6,MYB, SFRS6, GLRB, NDN, GNAQ, TUSC3, GNAQ, JARID2, OCRL, FHL1, EZH2,SMOX, SLC4A2, UFD1L, ZNF32, HTATSF1, SHD1, PTOV1, NXF1, FYB, TRIM28,BC008967, TRB@, H1F0, CD3D, CD3G, CENPB, ALDH2, ANXA1, H2AFX, CD1E,DDX5, CCNA2, ENO2, SNRPB, GATA3, RRM2, GLUL, SOX4, MAL, UNG, ARHGDIB,RUNX1, MPHOSPH6, DCTN1, SH3GL3, PLEKHC1, CD47, POLR2F, RHOH, and ADD1,or wherein the method further comprises measuring a level of expressionof at least one gene selected from the group consisting of ITK, RALY,PSMC5, MYL6, CD1B, STMN1, GNA15, MDK, CAPG, ACTN1, CTNNA1, FARSLA, E2F4,CPSF1, SEPW1, TFRC, ABL1, TCF7, FGFR1, NUCB2, SMA3, FAT, VIM, andATP2A3, wherein said level of expression of said gene indicates thatsaid cell is sensitive to Rituximab.
 22. The method of claim 1, whereinsaid at least one gene is selected from the group consisting of TRA1,ACTN4, CALM1, CD63, FKBP1A, CALU, IQGAP1, MGC8721, STAT1, TACC1, TM4SF8,CD59, CKAP4, DUSP1, RCN1, MGC8902, LGALS1, BHLHB2, RRBP1, PRNP, IER3,MARCKS, LUM, FER1L3, SLC20A1, HEXB, EXT1, TJP1, CTSL, SLC39A6, RIOK3,CRK, NNMT, TRAM2, ADAM9, DNAJC7, PLSCR1, PRSS23, PLOD2, NPC1, TOB1,GFPT1, IL8, PYGL, LOXL2, KIAA0355, UGDH, PURA, ULK2, CENTG2, NID2,CAP350, CXCL1, BTN3A3, IL6, WNT5A, FOXF2, LPHN2, CDH11, P4HA1, GRP58,DSIPI, MAP1LC3B, GALIG, IGSF4, IRS2, ATP2A2, OGT, TNFRSF10B, KIAA1128,TM4SF1, RBPMS, RIPK2, CBLB, NR1D2, SLC7A11, MPZL1, SSA2, NQO1, ASPH,ASAH1, MGLL, SERPINB6, HSPA5, ZFP36L1, COL4A1, CD44, SLC39A14, NIPA2,FKBP9, IL6ST, DKFZP564G2022, PPAP2B, MAP1B, MAPK1, MYO1B, CAST, RRAS2,QKI, LHFPL2, 38970, ARHE, KIAA1078, FTL, KIAA0877, PLCB1, KIAA0802,RAB3GAP, SERPINB1, TIMM17A, SOD2, HLA-A, NOMO2, LOC55831, PHLDA1, TMEM2,MLPH, FAD104, LRRC5, RAB7L1, FLJ35036, DOCK10, LRP12, TXNDC5, CDCl₄B,HRMT1L1, CORO1C, DNAJC10, TNPO1, LONP, AMIGO2, DNAPTP6, and ADAMTS1, orwherein the method further comprises measuring a level of expression ofat least one gene selected from the group consisting of WARS, CD81,CTSB, PKM2, PPP2CB, CNN3, ANXA2, JAK1, EIF4G3, COL1A1, DYRK2, NFIL3,ACTN1, CAPN2, BTN3A2, IGFBP3, FN1, COL4A2, and KPNB1, or wherein themethod further comprises measuring a level of expression of at least onemicroRNA selected from the group consisting of hsa-mir-136-prec, Hcd570,Hcd873, Hcd282PO, Hcd799, Hcd829, Hcd210_HPR205, hsa-mir-2,9-prec,hsa-mir-202, hsa-mir-429, Hcd693, hsa-mir-022-prec, MPR88,hsa-mir-198-prec, hsa-mir-199b-prec, Hcd145, hsa-mir-124a-2-prec,hsa-mir-138-2-prec, Hcd960, Hcd869, Hcd384, hsa-mir-027b-prec, Hcd444,hsa-mir-194-2, hsa-mir-197-prec, Hcd913, HPR163, hsa-mir-138-1-prec,hsa-mir-010a-prec, hsa-mir-023b-prec, hsa-mir-193b, Hcd654, Hcd542,hsa-mir-199a-2-prec, hsa-mir-2,4-prec, Hcd608, Hcd684, hsa-mir-145-prec,hsa-mir-023a-prec, hsa-mir-024-2-prec, and hsa-mir-199a-1-prec, whereinsaid level of expression of said gene or microRNA indicates that saidcell is sensitive to radiation therapy.
 23. The method of claim 1,wherein said at least one gene is selected from the group consisting ofFAU, NOL5A, ANP32A, ARHGDIB, LBR, FABP5, ITM2A, SFRS5, IQGAP2, SLC7A6,SLA, IL2RG, MFNG, GPSM3, PIM2, EVER1, LRMP, ICAM2, RIMS3, FMNL1, MYB,PTPN7, LCK, CXorf9, RHOH, ZNFN1A1, CENTB1, LCP2, DBT, CEP1, IL6R, VAV1,MAP4K1, CD28, PTP4A3, CD3G, LTB, USP34, NVL, CD8B1, SFRS6, LCP1, CXCR4,PSCDBP, SELPLG, CD3Z, PRKCQ, CD1A, GATA2, P2RX5, LAIR1, C1orf38, SH2D1A,TRB@, SEPT6, HA-1, DOCK2, WBSCR20C, CD3D, RNASE6, SFRS7, WBSCR20A,NUP210, CD6, HNRPA1, AIF1, CYFIP2, GLTSCR2, C11orf2, ARHGAP15, BIN2,SH3TC1, STAG3, TM6SF1, C15orf25, FLJ22457, PACAP, and MGC2744, orwherein the method further comprises measuring a level of expression ofat least one microRNA selected from the group consisting ofhsa-mir-092-prec-X=092-2, hsa-mir-123-prec, hsa-mir-106a, hsa-mir-20b,hsa-mir-0,7-prec, hsa-mir-019b-2-prec, hsa-mir-033-prec,hsa-mir-092-prec-13=092-1, hsa-mir-122a-prec, Hcd783, MPR216,hsa-mir-019b-1-prec, hsa-mir-135-2-prec, hsa-mir-128b-prec,hsa-mir-025-prec, Hcd511, hsa-mir-093-prec-7.1=093-1,hsa-mir-106-prec-X, hsa-mir-142-prec, HPR169, hsa-mir-223-prec,hsa-mir-018-prec, and hsa-mir-020-prec, wherein said level of expressionof said gene or microRNA indicates that said cell is sensitive to PXD101(belinostat).
 24. The method of claim 1, wherein said at least one geneis selected from the group consisting of CD99, SNRPA, CUGBP2, STAT5A,SLA, IL2RG, GTSE1, MYB, PTPN7, CXorf9, RHOH, ZNFN1A1, CENTB1, LCP2,HIST1H4C, CCR7, APOBEC3B, MCM7, LCP1, SELPLG, CD3Z, PRKCQ, GZMB, SCN3A,LAIR1, SH2D1A, SEPT6, CG018, CD3D, C18orf10, PRF1, AIF1, MCM5, LPXN,C22orf18, ARHGAP15, and LEF1, or wherein the method further comprisesmeasuring a level of expression of at least one microRNA selected fromthe group consisting of hsa-mir-096-prec-7, Hcd605, hsa-mir-20b,hsa-miR-373*, HUMTRAB, hsa-mir-019b-1-prec, HPR163, hsa-mir-371,hsa-mir-025-prec, hsa-mir-18b, hsa-mir-093-prec-7.1=093-1,hsa-mir-106-prec-X, hsa-mir-142-prec, and hsa-mir-020-prec, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to 5-Aza-2′-deoxycytidine (Decitabine).
 25. The method ofclaim 1, wherein said at least one gene is selected from the groupconsisting of SLC9A3R1, RPS19, ITM2A, SSBP2, CXorf9, RHOH, ZNFN1A1,FXYD2, CCR9, NAP1L1, CXCR4, SH2D1A, CD1A, TRB@, SEPT6, RPS2, DOCK2,CD3D, CD6, ZAP70, AIF1, CD1E, CYFIP2, ADA, TRIM, GLTSCR2, FLJ10858,BCL11B, GIMAP6, STAG3, UBASH3A or wherein the method further comprisesmeasuring a level of expression of at least one gene selected from thegroup consisting of MRPS24, TRIM22, TRIM41, LAT, CD1C, MRPS22, ADAM11,RPL13, RPS27, RPL13, RPS25, RPL18A, CORO1A, PTPRCAP, GMFG, ITK, CD1B,GMFG, PTPRCAP, CORO1A, ITGB2, HCLS1, and ATP2A3, or wherein the methodfurther comprises measuring a level of expression of at least onemicroRNA selected from the group consisting of HUMTRF, hsa-mir-483,MPR74, hsa-mir-122a-prec, ath-MIR180a, hsa-mir-128b-prec, Hcd923,hsa-mir-106-prec-X, hsa-mir-342, hsa-mir-142-prec, HPR169,hsa-mir-223-prec, Hcd754, and hsa-mir-020-prec, wherein said level ofexpression of said gene or microRNA indicates that said cell issensitive to Idarubicin.
 26. The method of claim 1, wherein said atleast one gene is selected from the group consisting of CD99, HLA-DPB1,ARHGDIB, IFITM1, UBE2L6, ITM2A, SERPINA1, STAT5A, INPP5D, DGKA, SATB1,SEMA4D, TFDP2, SLA, IL2RG, CD48, MFNG, ALOX5AP, GPSM3, PSMB9, KIAA0711,SELL, ADA, EDG1, RIMS3, FMNL1, MYB, PTPN7, LCK, CXorf9, RHOH, ZNFN1A1,CENTB1, LCP2, FXYD2, CD1D, BATF, STAT4, VAV1, MAP4K1, CCR7, PDE4C, CD3G,CCR9, SP110, LCP1, IFI16, CXCR4, ARHGEF6, GATA3, SELPLG, SEC31L2, CD3Z,PRKCQ, SH2D1A, GZMB, CD1A, SCN3A, LAIR1, FYB, TRB@, SEPT6, HA-1, DOCK2,CG018, CD3D, T3JAM, FNBP1, CD6, ZAP70, LST1, GPR65, PRF1, AIF1,FLJ20331, RAG2, WDR45, CD1E, CYFIP2, TARP, TRIM, RPL10L, GLTSCR2,GIMAP5, ARHGAP15, NOTCH1, BIN2, C13orf18, CECR1, BCL11B, GIMAP6, STAG3,TM6SF1, HSD17B7, UBASH3A, MGC5566, FLJ22457, TPK1, PHF11, andDKFZP434B0335, or wherein the method further comprises measuring a levelof expression of at least one gene selected from the group consisting ofFLJ10534, PTPRC, TRIM22, C18orf1, EVL, TRIM41, PSME2, LAT, CD1C,MYBBP1A, ICAM3, ADAM11, CD53, FARSLA, RPL13, RAC2, RPL13, GNA15, PGF,LAPTM5, RPL18A, CD53, CORO1A, PTPRCAP, PTPRC, HEM1, GMFG, GNA15, ITK,CD1B, GMFG, PTPRCAP, PTPRC, CD53, CORO1A, HEM1, GNA15, TCF7, ITGB2,PTPRC, HCLS1, ATP2A3, MYBL1, and FARSLA, or wherein the method furthercomprises measuring a level of expression of at least one microRNAselected from the group consisting of hsa-mir-124a-3-prec,hsa-mir-181a-prec, Hcd773, Hcd683, Hcd796, HUMTRF, HUMTRS,hsa-mir-181b-2, Hcd294, hsa-mir-20b, hsa-mir-181d, hsa-mir-2,3-prec,Hcd148_HPR225left, hsa-mir-515-15p, hsa-mir-181b-prec, Hcd783, HUMTRAB,HUMTRN, hsa-mir-181b-1, hsa-mir-124a-1-prec1, hsa-mir-367,hsa-mir-128b-prec, Hcd438right, hsa-mir-025-prec, hsa-mir-2,6-prec,Hcd731, hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X, hsa-mir-342,hsa-mir-142-prec, HSHELA01, HUMTRV1A, hsa-mir-223-prec, Hcd754, andhsa-mir-020-prec, wherein said level of expression of said gene ormicroRNA indicates that said cell is sensitive to Melphalan.
 27. Themethod of claim 1, wherein said at least one gene is selected from thegroup consisting of MCL1, DDX23, JUNB, ZFP36, IFITM1, CKS1B, SERPINA1,IL4R, CLDN3, ARL4A, HMMR, FLJ12671, ANKHD1, KIF2C, RPA3, MCCC2, CDH17,LSM5, PRF1, ROD1, FLJ12666, SUV420H1, MUC13, C13orf18, and CDCA8, orwherein the method further comprises measuring a level of expression ofat least one gene selected from the group consisting of ETS2, AR1D1A,ID1, DDC, NID2, CCT3, ID2, NFIL3, and AREG, or wherein the methodfurther comprises measuring a level of expression of at least onemicroRNA selected from the group consisting of Hcd829, hsa-mir-197-prec,HPR163, and hsa-mir-150-prec, wherein said level of expression of saidgene or microRNA indicates that said cell is sensitive to IL4-PE38fusion protein.
 28. The method of claim 1, wherein said at least onegene is selected from the group consisting of MCL1, DDX23, JUNB, ZFP36,IFITM1, CKS1B, SERPINA1, IL13R, CLDN3, ARL4A, HMMR, FLJ12671, ANKHD1,KIF2C, RPA3, MCCC2, CDH17, LSM5, PRF1, ROD1, FLJ12666, SUV420H1, MUC13,C13orf18, and CDCA8, or wherein the method further comprises measuring alevel of expression of at least one gene selected from the groupconsisting of ETS2, AR1D1A, ID1, DDC, NID2, CCT3, ID2, NFIL3, and AREG,or wherein the method further comprises measuring a level of expressionof at least one microRNA selected from the group consisting of Hcd829,hsa-mir-197-prec, HPR163, and hsa-mir-150-prec, wherein said level ofexpression of said gene or microRNA indicates that said cell issensitive to IL13-PE38QQR fusion protein (cintredekin besudotox). 29.The method of claim 1, wherein said at least one gene is selected fromthe group consisting of STOM, TNFAIP3, ASNS, GARS, CXCR4, EGLN3, LBH,and GDF15, or wherein the method further comprises measuring a level ofexpression of at least one gene selected from the group consisting ofSTOML1 and KIAA0746, or wherein the method further comprises measuring alevel of expression of at least one microRNA selected from the groupconsisting of hsa-mir-034prec, Hcd255, Hcd712, Hcd965, Hcd891,Hcd210_HPR205, hsa-mir-429, Hcd753, Hcd693, MPR203, Hcd704, Hcd863PO,hsa-mir-122a-prec, Hcd760, Hcd338, HPR213, Hcd852, Hcd366, MPR103,Hcd669, and hsa-mir-188-prec, wherein said level of expression of saidgene or microRNA indicates that said cell is sensitive to Valproic acid(VPA).
 30. The method of claim 1, wherein said at least one gene isselected from the group consisting of PPIB, ZFP36L2, IFI30, USP7, SRM,SH3BP5, ALDOC, FADS2, GUSB, PSCD1, IQGAP2, STS, MFNG, FLI1, PIM2,INPP4A, LRMP, ICAM2, EVI2A, MAL, BTN3A3, PTPN7, IL10RA, SPI1, TRAF1,ITGB7, ARHGAP6, MAP4K1, CD28, PTP4A3, LTB, C1orf38, WBSCR22, CD8B1,LCP1, FLJ13052, MEF2C, PSCDBP, IL16, SELPLG, MAGEA9, LAIR1, TNFRSF25,EVI2B, IGJ, PDCD4, RASA4, HA-1, PLCL2, RNASE6, WBSCR20C, NUP210, RPL10L,C11orf2, CABC1, ARHGEF3, TAPBPL, CHST12, FKBP11, FLJ35036, MYLIP,TXNDC5, PACAP, TOSO, PNAS-4, IL21R, and TCF4, or wherein the methodfurther comprises measuring a level of expression of at least one geneselected from the group consisting of CLTB, BTN3A2, BCL2, SETBP1, ICAM3,BCL2, BCL2, BCL2, CD53, CCND2, CLTB, CLTB, BCL2L11, BTN3A2, CD37, MYCL2,CTSS, LAPTM5, CD53, CORO1A, HEM1, CD53, CORO1A, HEM1, HCLS1, BCL2L11,MYCL1, MYC, and MAN1A1, or wherein the method further comprisesmeasuring a level of expression of at least one microRNA selected fromthe group consisting of Hcd257, hsa-mir-148-prec, Hcd512, HPR227,Hcd421, MPR203, hsa-mir-0,7-prec, hsa-mir-219-2, hsa-mir-328, Hcd783,Hcd181, HPR213, hsa-mir-191-prec, hsa-mir-375, hsa-mir-2,2-prec, Hcd913,Hcd716, MPR207, HPR206, hsa-mir-016b-chr3, Hcd654, hsa-mir-195-prec,Hcd425, hsa-mir-148a, hsa-mir-142-prec, and hsa-mir-016a-chr13, whereinsaid level of expression of said gene or microRNA indicates that saidcell is sensitive to All-trans retinoic acid (ATRA).
 31. The method ofclaim 1, wherein said at least one gene is selected from the groupconsisting of C6orf29, TRIM31, CD69, LRRN3, GPR35, and CDW52, or whereinthe method further comprises measuring a level of expression of at leastone microRNA selected from the group consisting of Hcd99,hsa-mir-520c/526a, hsa-mir-191-prec, hsa-mir-205-prec, hsa-mir-375,hsa-mir-423, hsa-mir-449, and hsa-mir-196-2-prec, wherein said level ofexpression of said gene or microRNA indicates that said cell issensitive to Cytoxan.
 32. The method of claim 1, wherein said at leastone gene is selected from the group consisting of K-ALPHA-1, CSDA,UCHL1, NAP1L1, ATP5G2, HDGFRP3, and IFI44, or wherein the method furthercomprises measuring a level of expression of at least one microRNAselected from the group consisting of HUMTRF, MPR74, hsa-mir-2,3-prec,hsa-mir-155-prec, hsa-mir-181b-prec, hsa-mir-342, and hsa-mir-4323p,wherein said level of expression of said gene or microRNA indicates thatsaid cell is sensitive to Topotecan (Hycamtin).
 33. The method of claim1, wherein said at least one gene is selected from the group consistingof NOL5A, STOM, SIAT1, CUGBP2, GUSB, ITM2A, JARID2, RUNX3, ICAM2, PTPN7,VAV1, PTP4A3, MCAM, MEF2C, IDH3B, RFP, SEPT6, SLC43A3, WBSCR20C, SHMT2,GLTSCR2, CABC1, FLJ20859, FLJ20010, MGC10993, and FKBP11, or wherein themethod further comprises measuring a level of expression of at least onegene selected from the group consisting of STOML1, EIF4A1, PDE3B,BCL11A, INPP4B, HLA-DMA, TRFP, EIF4A1, GAS7, MYCL2, HCLS1, MYCL1, andMYC, or wherein the method further comprises measuring a level ofexpression of at least one microRNA selected from the group consistingof hsa-mir-092-prec-X=092-2, hsa-mir-123-prec, hsa-mir-514-1,hsa-mir-101-prec-9, hsa-mir-148-prec, hsa-mir-106a, hsa-mir-20b, Hcd781,hsa-mir-0,7-prec, hsa-mir-019b-2-prec, hsa-mir-033-prec,hsa-mir-092-prec-13=092-1, hsa-mir-107, hsa-mir-103-prec-5=103-1,MPR216, hsa-mir-29b-2=102prec7.1=7.2, hsa-mir-019b-1-prec,hsa-mir-107-prec-10, hsa-mir-135-2-prec, Hcd581, hsa-mir-103-2-prec,Hcd230, hsa-mir-025-prec, hsa-mir-208-prec, hsa-mir-18b,hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X, hsa-mir-142-prec,HPR169, hsa-mir-0,8-prec, and hsa-mir-020-prec, wherein said level ofexpression of said gene or microRNA indicates that said cell issensitive to Suberoylanilide hydroxamic acid (SAHA, vorinostat,Zolinza).
 34. The method of claim 1, wherein said at least one gene isselected from the group consisting of ZFP36L2, TRIB2, LCP2, C6orf32,IL16, CACNA1G, SPDEF, HAB1, TOSO, and ARHGAP25, or wherein the methodfurther comprises measuring a level of expression of at least one geneselected from the group consisting of SGCD and CAPN3, or wherein themethod further comprises measuring a level of expression of at least onemicroRNA selected from the group consisting of Hcd415, hsa-mir-147-prec,hsa-mir-033b-prec, Hcd778, hsa-mir-127-prec, hsa-mir-324, Hcd794, andHcd634, wherein said level of expression of said gene or microRNAindicates that said cell is sensitive to Depsipeptide (FR901228). 35.The method of claim 1, wherein said at least one gene is selected fromthe group consisting of PLEKHB2, ARPC1B, MX1, CUGBP2, IFI16, TNFRSF14,SP110, ELF1, LPXN, IFRG28, LEF1, and PYCARD, or wherein the methodfurther comprises measuring a level of expression of HMX1, or whereinthe method further comprises measuring a level of expression of at leastone microRNA selected from the group consisting of MPR121, Hcd115,Hcd693, Hcd704, HPR100, Hcd760, hsa-mir-147-prec, hsa-mir-033b-prec,hsa-mir-146-prec, Hcd142, hsa-mir-501, Hcd716, MPR207, Hcd777,hsa-mir-204-prec, hsa-mir-146b, Hcd511, Hcd397, MPR130, Hcd782,hsa-mir-324, Hcd794, and Hcd739, wherein said level of expression ofsaid gene or microRNA indicates that said cell is sensitive toBortezomib.
 36. The method of claim 1, wherein said at least one gene isselected from the group consisting of SSRP1, ALDOC, C1QR1, TTF1, PRIM1,USP34, TK2, GOLGIN-67, NPDO14, KIAA0220, SLC43A3, WBSCR20C, ICAM2,TEX10, CHD7, SAMSN1, and TPRT, or wherein the method further comprisesmeasuring a level of expression of at least one gene selected from thegroup consisting of PTPRC, CD53, RNPS1, H3F3A, NUDC, SMARCA4, RPL32,PTMA, CD53, PTPRCAP, PTPRC, RPL32, PTPRCAP, PTPRC, CD53, PTPRC, HCLS1,and SLC19A1, or wherein the method further comprises measuring a levelof expression of at least one microRNA selected from the groupconsisting of hsa-mir-092-prec-X=092-2, hsa-mir-096-prec-7,hsa-mir-123-prec, MPR249, HPR232, hsa-mir-101-prec-9, hsa-mir-106a,hsa-mir-20b, Hcd861, hsa-mir-017-prec, hsa-mir-019b-2-prec,hsa-mir-033-prec, Hcd102, MPR216, Hcd975, hsa-mir-019b-1-prec,hsa-mir-135-2-prec, Hcd581, Hcd536_HPR104, hsa-mir-128b-prec, HSTRNL,hsa-mir-025-prec, hsa-mir-18b, HPR262, Hcd923, Hcd434, Hcd658, HPR129,hsa-mir-380-5p, hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X, Hcd627,hsa-mir-142-prec, hsa-mir-018-prec, and hsa-mir-020-prec, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to Leukeran.
 37. The method of claim 1, wherein said at leastone gene is selected from the group consisting of HLA-E, BAT3, ENO2,UBE2L6, CUGBP2, ITM2A, PALM2-AKAP2, JARID2, DGKA, SLC7A6, TFDP2, ADA,EDG1, ICAM2, PTPN7, CXorf9, RHOH, MX2, ZNFN1A1, COCH, LCP2, CLGN, BNC1,FLNC, HLA-DRB3, UCP2, HLA-DRB1, GATA3, PRKCQ, SH2D1A, NFATC3, TRB@,FNBP1, SEPT6, NME4, DKFZP434C171, ZC3HAV1, SLC43A3, CD3D, AIF1, SPTAN1,CD1E, TRIM, DATF1, FHOD1, ARHGAP15, STAG3, SAP130, and CYLD, or whereinthe method further comprises measuring a level of expression of at leastone gene selected from the group consisting of PTPRC, MX2004PA11424,TRIM22, TRIM41, CD1C, CHD8, ADAM11, ANPEP, RBMX2, RAC2, GNA15, LAPTM5,PTPRCAP, PTPRC, GNA15, CD1B, PTPRCAP, PTPRC, GNA15, PTPRC, and ATP2A3,or wherein the method further comprises measuring a level of expressionof at least one microRNA selected from the group consisting of Hcd773,Hcd248, hsa-mir-181d, MPR74, hsa-mir-2,3-prec, hsa-mir-155-prec, MPR197,hsa-mir-181b-prec, hsa-mir-29b-2=102prec7.1=7.2, hsa-mir-029c-prec,Hcd318, hsa-mir-128b-prec, hsa-mir-130a-prec, hsa-mir-140, hsa-mir-16-2,hsa-mir-526a-2, hsa-mir-016b-chr3, hsa-mir-195-prec, hsa-mir-2,6-prec,hsa-mir-342, hsa-mir-29b-1, Hcd627, hsa-mir-102-prec-1,hsa-mir-142-prec, hsa-mir-223-prec, hsa-let-7f-2-prec2, andhsa-mir-016a-chr13, wherein said level of expression of said gene ormicroRNA indicates that said cell is sensitive to Fludarabine.
 38. Themethod of claim 1, wherein said at least one gene is CD99, or whereinthe method further comprises measuring a level of expression of at leastone microRNA selected from the group consisting of Hcd794 and Hcd754,wherein said level of expression of said gene or microRNA indicates thatsaid cell is sensitive to Vinblastine.
 39. The method of claim 1,wherein said at least one gene is selected from the group consisting ofRPLP2, BTG1, CSDA, ARHGDIB, INSIG1, ALDOC, WASPIP, C1QR1, EDEM1, SLA,MFNG, GPSM3, ADA, LRMP, EVI2A, FMNL1, PTPN7, RHOH, ZNFN1A1, CENTB1,MAP4K1, CD28, SP110, NAP1L1, IFI16, ARHGEF6, SELPLG, CD3Z, SH2D1A,LAIR1, RAFTLIN, HA-1, DOCK2, CD3D, T3JAM, ZAP70, GPR65, CYFIP2, LPXN,RPL10L, GLTSCR2, ARHGAP15, BCL11B, TM6SF1, PACAP, and TCF4, or whereinthe method further comprises measuring a level of expression of at leastone gene selected from the group consisting of PTPRC, BCL2, LAT, ICAM3,BCL2, BCL2, BCL2, ADAM11, CD53, FARSLA, BCL2L11, RPL13, RAC2, RPL13,MYCL2, LAPTM5, RPL18A, CD53, CORO1A, PTPRCAP, PTPRC, HEM1, GMFG, GMFG,PTPRCAP, PTPRC, CD53, CORO1A, HEM1, PTPRC, HCLS1, BCL2L11, MYCL1,FARSLA, and MYC, or wherein the method further comprises measuring alevel of expression of at least one microRNA selected from the groupconsisting of hsa-mir-096-prec-7, hsa-mir-124a-3-prec,hsa-mir-101-prec-9, Hcd712, Hcd693, hsa-mir-219-2, Hcd145,hsa-mir-155-prec, HPR213, hsa-mir-2,2-prec, Hcd913, Hcd716, MPR207,Hcd559, Hcd654, Hcd739, and hsa-mir-142-prec, wherein said level ofexpression of said gene or microRNA indicates that said cell issensitive to Busulfan.
 40. The method of claim 1, wherein said at leastone gene is selected from the group consisting of ARHGDIB, ITM2A, SSBP2,PIM2, SELL, ICAM2, EVI2A, MAL, PTPN7, ZNFN1A1, LCP2, ARHGAP6, CD28,CD8B1, LCP1, NPDO14, CD69, NFATC3, TRB@, IGJ, SLC43A3, DOCK2, FHOD1, andPACAP, or wherein the method further comprises measuring a level ofexpression of at least one gene selected from the group consisting ofICAM3, CD53, SMARCA4, CD37, LAPTM5, CD53, CORO1A, HEM1, GMFG, GMFG,CD53, CORO1A, HEM1, and HCLS1, or wherein the method further comprisesmeasuring a level of expression of at least one microRNA selected fromthe group consisting of hsa-mir-092-prec-X=092-2, hsa-mir-123-prec,hsa-mir-101-prec-9, Hcd517, Hcd796, Hcd749, Hcd674, hsa-mir-019b-2-prec,hsa-mir-033-prec, hsa-mir-092-prec-13=092-1, hsa-mir-124a-2-prec,hsa-mir-143-prec, hsa-mir-516-43p, hsa-mir-2,6-prec, Hcd731,hsa-mir-106-prec-X, hsa-mir-142-prec, hsa-mir-223-prec, Hcd754, andhsa-mir-018-prec, wherein said level of expression of said gene ormicroRNA indicates that said cell is sensitive to Dacarbazine.
 41. Themethod of claim 1, wherein said at least one gene is selected from thegroup consisting of RPL18, RPL10A, RPS3A, EEF1B2, GOT2, RPL13A, RPS15,NOL5A, RPLP2, SLC9A3R1, EIF3S3, MTHFD2, IMPDH2, ALDOC, FABP5, ITM2A,PCK2, MFNG, GCH1, PIM2, ADA, ICAM2, TTF1, MYB, PTPN7, RHOH, ZNFN1A1,PRIM1, FHIT, ASS, SYK, OXA1L, LCP1, DDX18, NOLA2, KIAA0922, PRKCQ,NFATC3, ANAPC5, TRB@, CXCR4, FNBP4, SEPT6, RPS2, MDN1, PCCB, RASA4,WBSCR20C, SFRS7, WBSCR20A, NUP210, SHMT2, RPLP0, MAP4K1, HNRPA1, CYFIP2,RPL10L, GLTSCR2, MRPL16, MRPS2, FLJ12270, CDK5RAP3, ARHGAP15, CUTC,FKBP11, ADPGK, FLJ22457, PUS3, PACAP, and CALML4, or wherein the methodfurther comprises measuring a level of expression of at least one geneselected from the group consisting of MRPS24, DUSP2, EIF4A1, BRD2,BCL11A, RASSF2, MRPL37, MRPL30, RASSF1, MYBBP1A, LASS2, MRPS22, ADAM11,CD53, RPS6 KB1, RNPS1, BRD2, EIF4A1, FBL, BRD2, RPL36A, RPL13, RPL38,H3F3A, KIAA0182, RPS27, RPS6, EEF1G, RPL13, MYCL2, FBLN1, RPS25, RPL32,PTMA, RPL18A, RPL3, CD53, CORO1A, HEM1, GMFG, RPL32, GMFG, CD53, CORO1A,HEM1, HCLS1, ATP2A3, RASSF7, MYCL1, MYBL1, MYC, RPS15A, RASSF2, andLASS6, or wherein the method further comprises measuring a level ofexpression of at least one microRNA selected from the group consistingof hsa-mir-092-prec-X=092-2, hsa-mir-148-prec, hsa-mir-20b,hsa-mir-007-2-prec, hsa-mir-0,7-prec, hsa-mir-019b-2-prec, Hcd760,Hcd783, MPR216, hsa-mir-375, hsa-mir-019b-1-prec, hsa-mir-135-2-prec,hsa-mir-150-prec, hsa-mir-128b-prec, hsa-mir-499, hsa-mir-025-prec,hsa-mir-007-1-prec, hsa-mir-019a-prec, hsa-mir-093-prec-7.1=093-1,hsa-mir-106-prec-X, hsa-mir-142-prec, HPR169, hsa-mir-018-prec,hsa-mir-020-prec, and hsa-mir-484, wherein said level of expression ofsaid gene or microRNA indicates that said cell is sensitive toOxaliplatin.
 42. The method of claim 1, wherein said at least one geneis selected from the group consisting of CSDA, INSIG1, UBE2L6, PRG1,ITM2A, DGKA, SLA, PCBP2, IL2RG, ALOX5AP, PSMB9, LRMP, ICAM2, PTPN7,CXorf9, RHOH, ZNFN1A1, CENTB1, LCP2, STAT4, CCR7, CD3G, SP110, TNFAIP8,IFI16, CXCR4, ARHGEF6, SELPLG, CD3Z, PRKCQ, SH2D1A, CD1A, NFATC3, LAIR1,TRB@, SEPT6, RAFTLIN, DOCK2, CD3D, CD6, AIF1, CD1E, CYFIP2, TARP, ADA,ARHGAP15, GIMAP6, STAG3, FLJ22457, PACAP, and TCF4, or wherein themethod further comprises measuring a level of expression of at least onegene selected from the group consisting of PTPRC, TRIM22, PSME2, LAT,CD1C, ICAM3, ADAM11, CD53, FARSLA, RPL13, RAC2, RPL13, NK4, LAPTM5,CD53, CORO1A, PTPRCAP, PTPRC, HEM1, GMFG, GMFG, PTPRCAP, PTPRC, CD53,CORO1A, HEM1, ITGB2, PTPRC, HCLS1, ATP2A3, and FARSLA, or wherein themethod further comprises measuring a level of expression of at least onemicroRNA selected from the group consisting of Hcd257, Hcd768, Hcd796,HUMTRF, HUMTRS, MPR74, hsa-mir-2,3-prec, hsa-mir-155-prec, Hcd763,hsa-mir-181b-prec, ath-MIR180a, hsa-mir-2,6-prec, hsa-mir-342,hsa-mir-142-prec, HSHELA01, HUMTRV1A, hsa-mir-223-prec, Hcd754, andhsa-mir-020-prec, wherein said level of expression of said gene ormicroRNA indicates that said cell is sensitive to Hydroxyurea.
 43. Themethod of claim 1, wherein said at least one gene is selected from thegroup consisting of RPL11, RPL17, ANAPC5, RPL13A, STOM, TUFM, SCARB1,FABP5, KIAA0711, IL6R, WBSCR22, UCK2, GZMB, C1orf38, PCBP2, GPR65,GLTSCR2, and FKBP11, or wherein the method further comprises measuring alevel of expression of at least one gene selected from the groupconsisting of STOML1, MRPL37, MRPL30, RPL36A, RPL38, HSPD1, MIF, RPL32,RPL3, and RPL32, or wherein the method further comprises measuring alevel of expression of at least one microRNA selected from the groupconsisting of Hcd257, Hcd946, Hcd503, hsa-mir-429, Hcd693, hsa-miR-373*,Hcd738, hsa-mir-328, Hcd783, Hcd181, Hcd631, Hcd279, hsa-mir-194-2,hsa-mir-197-prec, HPR163, hsa-mir-150-prec, Hcd323, hsa-mir-103-2-prec,Hcd243, Hcd938, hsa-mir-025-prec, hsa-mir-007-1-prec, MPR243, Hcd511,Hcd654, hsa-mir-199a-2-prec, hsa-mir-2,4-prec,hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X, Hcd794, Hcd530,HSHELA01, Hcd754, and hsa-mir-020-prec, wherein said level of expressionof said gene or microRNA indicates that said cell is sensitive toTegafur.
 44. The method of claim 1, wherein said at least one gene isselected from the group consisting of ALDOC, ITM2A, SLA, SSBP2, IL2RG,MFNG, SELL, STC1, LRMP, MYB, PTPN7, CXorf9, RHOH, ZNFN1A1, CENTB1,MAP4K1, CCR7, CD3G, CCR9, CBFA2T3, CXCR4, ARHGEF6, SELPLG, SEC31L2,CD3Z, SH2D1A, CD1A, SCN3A, LAIR1, TRB@, DOCK2, WBSCR20C, CD3D, T3JAM,CD6, ZAP70, GPR65, AIF1, WDR45, CD1E, CYFIP2, TARP, TRIM, ARHGAP15,NOTCH1, STAG3, UBASH3A, MGC5566, and PACAP, or wherein the methodfurther comprises measuring a level of expression of at least one geneselected from the group consisting of PTPRC, TRIM22, TRIM41, LAT, CD1C,MYBBP1A, CD53, FARSLA, PPP2CA, LAPTM5, CD53, CORO1A, PTPRCAP, PTPRC,HEM1, GMFG, ITK, CD1B, GMFG, PTPRCAP, PTPRC, CD53, CORO1A, HEM1, TCF7,PTPRC, HCLS1, ATP2A3, MYBL1, and FARSLA, or wherein the method furthercomprises measuring a level of expression of at least one microRNAselected from the group consisting of Hcd768, HUMTRF, Hcd145, Hcd923,hsa-mir-2,6-prec, hsa-mir-093-prec-7.1=093-1, hsa-mir-342, Hcd794,hsa-mir-142-prec, HSHELA01, hsa-mir-223-prec, and Hcd754, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to Daunorubicin.
 45. The method of claim 1, wherein said atleast one gene is selected from the group consisting of PFN1, CALU, ZYX,PSMD2, RAP1B, EPAS1, PGAM1, STAT1, CKAP4, DUSP1, RCN1, UCHL1, ITGA5,NFKBIA, LAMB1, TGFBI, FHL1, GJA1, PRG1, EXT1, MVP, NNMT, TAP1, CRIM1,PLOD2, RPS19, AXL, PALM2-AKAP2, IL8, LOXL2, PAPSS2, CAV1, F2R, PSMB9,LOX, C1orf29, STC1, LIF, KCNJ8, SMAD3, HPCAL1, WNT5A, BDNF, TNFRSF1A,NCOR2, FLNC, HMGA2, HLA-B, FLOT1, PTRF, IFI16, MGC4083, TNFRSF10B,PNMA2, TFPI, CLECSF2, SP110, PLAUR, ASPH, FSCN1, HIC, HLA-C, COL6A1,IL6ST, IFITM3, MAP1B, FLJ46603, RAFTLIN, FTL, KIAA0877, MT1E, CDC10,ZNF258, BCAT1, IFI44, SOD2, TMSB10, FLJ10350, C1orf24, EFHD2, RPS27L,TNFRSF12A, FAD104, RAB7L1, NME7, TMEM22, TPK1, ELK3, CYLD, AMIGO2,ADAMTS1, and ACTB, or wherein the method further comprises measuring alevel of expression of at least one gene selected from the groupconsisting of ACLY, MPZL1, STC2, BAX, RAB31, RAB31, (UBC12, LOXL1, EMP3,FGFR1OP, IL6, TRIM22, OPTN, CYR61, METAP1, SHC1, FN1, EMP3, RAB31,LOXL1, BAX, BAX, RAB31, FN1, CD44, ANXA1, COL5A2, LGALS1, FGFR1, PLAU,TFPI2, TFPI2, VCAM1, SHC1, CSF2RA, EMP3, COL1A1, TGFB1, COL6A2, FGFR1,ITGA3, AKR1B1, MSN, EMP3, VIM, EMP3, COL6A2, MSN, PSMC5, UBC, FGFR1,BASP1, ANXA11, CSPG2, M6PRBP1, PRKCA, OPTN, OPTN, SPARC, CCL2, andITGA3, or wherein the method further comprises measuring a level ofexpression of at least one microRNA selected from the group consistingof hsa-mir-125b-2-prec, hsa-mir-022-prec, hsa-mir-125b-1,hsa-mir-155-prec, hsa-mir-100, hsa-mir-409-3p, hsa-mir-495,hsa-mir-199a-2-prec, hsa-mir-382, and hsa-mir-100-1/2-prec, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to Bleomycin.
 46. The method of claim 1, wherein said at leastone gene is selected from the group consisting of HSPCB, LDHA, andTM4SF7, or wherein the method further comprises measuring a level ofexpression of LY6E, or wherein the method further comprises measuring alevel of expression of at least one microRNA selected from the groupconsisting of Hcd338, hsa-mir-099b-prec-19, and hsa-mir-149-prec,wherein said level of expression of said gene or microRNA indicates thatsaid cell is sensitive to Estramustine.
 47. The method of claim 1,wherein said at least one gene is selected from the group consisting ofCSDA, INSIG1, UBE2L6, PRG1, ITM2A, DGKA, TFDP2, SLA, IL2RG, ALOX5AP,GPSM3, PSMB9, SELL, ADA, EDG1, FMNL1, PTPN7, CXorf9, RHOH, ZNFN1A1,CENTB1, LCP2, CD1D, STAT4, VAV1, MAP4K1, CCR7, PDE4C, CD3G, CCR9, SP110,TNFAIP8, LCP1, IFI16, CXCR4, ARHGEF6, SELPLG, SEC31L2, CD3Z, PRKCQ,SH2D1A, GZMB, CD1A, LAIR1, AF1Q, TRB@, SEPT6, DOCK2, RPS19, CD3D, T3JAM,FNBP1, CD6, ZAP70, LST1, BCAT1, PRF1, AIF1, RAG2, CD1E, CYFIP2, TARP,TRIM, GLTSCR2, GIMAP5, ARHGAP15, NOTCH1, BCL11B, GIMAP6, STAG3, TM6SF1,UBASH3A, MGC5566, FLJ22457, and TPK1, or wherein the method furthercomprises measuring a level of expression of at least one gene selectedfrom the group consisting of PTPRC, TRIM22, EVL, TRIM41, PSME2, LAT,CD1C, ADAM11, CD53, FARSLA, RPL13, RAC2, RPL13, GNA15, LAPTM5, RPL18A,CD53, CORO1A, PTPRCAP, PTPRC, HEM1, GMFG, GNA15, ITK, CD1B, GMFG,PTPRCAP, PTPRC, CD53, CORO1A, HEM1, GNA15, ITGB2, PTPRC, HCLS1, ATP2A3,and FARSLA, or wherein the method further comprises measuring a level ofexpression of at least one microRNA selected from the group consistingof hsa-mir-181a-prec, hsa-mir-181c-prec, HUMTRF, hsa-mir-181d, MPR74,Hcd817, hsa-mir-2,3-prec, hsa-mir-155-prec, Hcd148_HPR225left,hsa-mir-515-15p, hsa-mir-181b-prec, HUMTRN, hsa-mir-128b-prec,hsa-mir-450-2, hsa-mir-2,6-prec, hsa-mir-342, hsa-mir-142-prec,hsa-mir-223-prec, Hcd754, and hsa-mir-020-prec, wherein said level ofexpression of said gene or microRNA indicates that said cell issensitive to Chlorambucil.
 48. The method of claim 1, wherein said atleast one gene is selected from the group consisting of PRG1, SLC2A3,RPS19, PSMB10, ITM2A, DGKA, SEMA4D, SLA, IL2RG, MFNG, ALOX5AP, GPSM3,PSMB9, SELL, ADA, FMNL1, MYB, PTPN7, CXorf9, RHOH, ZNFN1A1, CENTB1,FXYD2, CD1D, STAT4, MAP4K1, CCR7, PDE4C, CD3G, CCR9, SP110, TK2,TNFAIP8, NAP1L1, SELPLG, SEC31L2, CD3Z, PRKCQ, SH2D1A, GZMB, CD1A,LAIR1, TRB@, SEPT6, DOCK2, CG018, WBSCR20C, CD3D, CD6, LST1, GPR65,PRF1, ALMS1, AIF1, CD1E, CYFIP2, TARP, GLTSCR2, FLJ12270, ARHGAP15,NAP1L2, CECR1, GIMAP6, STAG3, TM6SF1, C15orf25, MGC5566, FLJ22457, ET,TPK1, and PHF11, or wherein the method further comprises measuring alevel of expression of at least one gene selected from the groupconsisting of ETS2, PTPRC, PETER, SETBP1, LAT, MYBBP1A, ETV5, METAP1,ETS1, ADAM11, CD53, FARSLA, RPL13, ARMET, TETRAN, BET1, RPL13, MET,LAPTM5, CD53, CORO1A, PTPRCAP, PTPRC, HEM1, GMFG, CD1B, GMFG, PTPRCAP,PTPRC, CD53, CORO1A, HEM1, ETV4, ITGB2, PTPRC, HCLS1, MYBL1, FARSLA, andMETAP2, or wherein the method further comprises measuring a level ofexpression of at least one microRNA selected from the group consistingof hsa-mir-124a-3-prec, Hcd946, Hcd683, HPR264, MPR185, HUMTRF, Hcd294,Hcd503, hsa-mir-20b, MPR74, MPR234, Hcd447, Hcd817, Hcd148_HPR225left,hsa-mir-515-15p, Hcd383, hsa-mir-181b-prec, Hcd783, MPR224, HPR172,MPR216, HUMTRN, hsa-mir-321, HPR159, MPR228, ath-MIR180a,hsa-mir-197-prec, hsa-mir-124a-1-prec1, hsa-mir-128b-prec,Hcd28_HPR39left, Hcd889, Hcd350, hsa-mir-025-prec, hsa-mir-208-prec,hsa-mir-450-2, Hcd923, Hcd434, HPR129, HPR220, hsa-mir-380-5p,hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X, hsa-mir-342,hsa-mir-142-prec, HSHELA01, hsa-mir-223-prec, Hcd754, hsa-mir-020-prec,and hsa-mir-4323p, wherein said level of expression of said gene ormicroRNA indicates that said cell is sensitive to Mechlorethamine. 49.The method of claim 1, wherein said at least one gene is selected fromthe group consisting of PGK1, SCD, INSIG1, IGBP1, TNFAIP3, TNFSF10,ABCA1, AGA, ABCA8, DBC1, PTGER2, UGT1A3, C10orf10, TM4SF13, CGI-90, LXN,DNAJC12, HIPK2, and C9orf95, or wherein the method further comprisesmeasuring a level of expression of at least one gene selected from thegroup consisting of FGFR1OP, PLXNA1, PSCD2L, TUBB, FGFR1, TUBB2, PAGA,TUBB2, UBB, TUBB2, FGFR1, FGFR1, and TUBB-PARALOG, or wherein the methodfurther comprises measuring a level of expression of at least onemicroRNA selected from the group consisting of hsa-mir-483, Hcd631,hsa-mir-2,2-prec, Hcd938, MPR133, Hcd794, Hcd438, and Hcd886, whereinsaid level of expression of said gene or microRNA indicates that saidcell is sensitive to Streptozocin.
 50. The method of claim 1, whereinsaid at least one gene is selected from the group consisting of RPLP2,CD99, IFITM1, INSIG1, ALDOC, ITM2A, SERPINA1, C1QR1, STAT5A, INPP5D,SATB1, VPS16, SLA, IL2RG, MFNG, SELL, LRMP, ICAM2, MYB, PTPN7, ARHGAP25,LCK, CXorf9, RHOH, ZNFN1A1, CENTB1, ADD2, LCP2, SPI1, DBT, GZMA, CD2,BATF, HIST1H4C, ARHGAP6, VAV1, MAP4K1, CCR7, PDE4C, CD3G, CCR9, SP140,TK2, LCP1, IFI16, CXCR4, ARHGEF6, PSCDBP, SELPLG, SEC31L2, CD3Z, PRKCQ,SH2D1A, GZMB, CD1A, GATA2, LY9, LAIR1, TRB@, SEPT6, HA-1, SLC43A3,DOCK2, CG018, MLC1, CD3D, T3JAM, CD6, ZAP70, DOK2, LST1, GPR65, PRF1,ALMS1, AIF1, PRDX2, FLJ12151, FBXW12, CD1E, CYFIP2, TARP, TRIM, RPL10L,GLTSCR2, CKIP-1, NRN1, ARHGAP15, NOTCH1, PSCD4, C13orf18, BCL11B,GIMAP6, STAG3, NARF, TM6SF1, C15orf25, FLJ11795, SAMSN1, UBASH3A, PACAP,LEF1, IL21R, TCF4, and DKFZP434B0335, or wherein the method furthercomprises measuring a level of expression of at least one gene selectedfrom the group consisting of FLJ10534, PTPRC, CD27BP, TRIM22, TRIM41,PSCD2L, CD1C, MYBBP1A, ICAM3, CD53, FARSLA, GAS7, ABCD2, CD24, CD29,RAC2, CD37, GNA15, PGF, LAPTM5, RPL18A, CD53, CORO1A, PTPRCAP, PTPRC,HEM1, GMFG, GNA15, ITK, GMFG, PTPRCAP, PTPRC, CD53, CORO1A, HEM1, GNA15,TCF7, ITGB2, PTPRC, HCLS1, PRKCB1, ATP2A3, PRKCB1, MYBL1, and FARSLA, orwherein the method further comprises measuring a level of expression ofat least one microRNA selected from the group consisting ofhsa-mir-092-prec-X=092-2, Hcd517, Hcd796, HUMTRF, hsa-mir-20b,hsa-mir-019b-2-prec, hsa-mir-033-prec, hsa-mir-092-prec-13=092-1,Hcd148_HPR225left, HUMTRAB, Hcd975, hsa-mir-135-2-prec,hsa-mir-128b-prec, hsa-mir-143-prec, hsa-mir-025-prec, hsa-mir-2,6-prec,hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X, hsa-mir-142-prec,HSHELA01, HUMTRV1A, hsa-mir-223-prec, Hcd754, hsa-mir-018-prec, andhsa-mir-020-prec, wherein said level of expression of said gene ormicroRNA indicates that said cell is sensitive to Carmustine.
 51. Themethod of claim 1, wherein said at least one gene is selected from thegroup consisting of RPS15, INSIG1, ALDOC, ITM2A, C1QR1, STAT5A, INPP5D,VPS16, SLA, USP20, IL2RG, MFNG, LRMP, EVI2A, PTPN7, ARHGAP25, RHOH,ZNFN1A1, CENTB1, LCP2, SPI1, ARHGAP6, MAP4K1, CCR7, LY96, C6orf32,MAGEA1, SP140, LCP1, IFI16, ARHGEF6, PSCDBP, SELPLG, CD3Z, PRKCQ, GZMB,LAIR1, SH2D1A, TRB@, RFP, SEPT6, HA-1, SLC43A3, CD3D, T3JAM, GPR65,PRF1, AIF1, LPXN, RPL10L, SITPEC, ARHGAP15, C13orf18, NARF, TM6SF1,PACAP, and TCF4, or wherein the method further comprises measuring alevel of expression of at least one gene selected from the groupconsisting of PTPRC, ICAM3, TRFP, CD53, FARSLA, RAC2, MAGEA11, LAPTM5,CD53, CORO1A, PTPRCAP, PTPRC, HEM1, GMFG, GMFG, PTPRCAP, PTPRC, CD53,CORO1A, HEM1, PTPRC, HCLS1, SLC19A1, FARSLA, and RPS15A, or wherein themethod further comprises measuring a level of expression of at least onemicroRNA selected from the group consisting of hsa-mir-101-prec-9,Hcd796, hsa-mir-20b, HUMTRAB, hsa-mir-135-2-prec, hsa-mir-153-1-prec1,hsa-mir-025-prec, hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X,hsa-mir-142-prec, HUMTRV1A, Hcd754, hsa-mir-018-prec, andhsa-mir-020-prec, wherein said level of expression of said gene ormicroRNA indicates that said cell is sensitive to Lomustine.
 52. Themethod of claim 1, wherein said at least one gene is selected from thegroup consisting of SSRP1, ALDOC, C1QR1, TTF1, PRIM1, USP34, TK2,GOLGIN-67, NPDO14, KIAA0220, SLC43A3, WBSCR20C, ICAM2, TEX10, CHD7,SAMSN1, and TPRT, or wherein the method further comprises measuring alevel of expression of at least one gene selected from the groupconsisting of PTPRC, CD53, RNPS1, H3F3A, NUDC, SMARCA4, RPL32, PTMA,CD53, PTPRCAP, PTPRC, RPL32, PTPRCAP, PTPRC, CD53, PTPRC, HCLS1, andSLC19A1, or wherein the method further comprises measuring a level ofexpression of at least one microRNA selected from the group consistingof hsa-mir-092-prec-X=092-2, hsa-mir-096-prec-7, hsa-mir-123-prec,MPR249, HPR232, hsa-mir-101-prec-9, hsa-mir-106a, hsa-mir-20b, Hcd861,hsa-mir-0,7-prec, hsa-mir-019b-2-prec, hsa-mir-033-prec, Hcd102, MPR216,Hcd975, hsa-mir-019b-1-prec, hsa-mir-135-2-prec, Hcd581, Hcd536_HPR104,hsa-mir-128b-prec, HSTRNL, hsa-mir-025-prec, hsa-mir-18b, HPR262,Hcd923, Hcd434, Hcd658, HPR129, hsa-mir-380-5p,hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X, Hcd627,hsa-mir-142-prec, hsa-mir-018-prec, and hsa-mir-020-prec, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to Mercaptopurine.
 53. The method of claim 1, wherein said atleast one gene is selected from the group consisting of CD99, INSIG1,PRG1, ALDOC, ITM2A, SLA, SSBP2, IL2RG, MFNG, ALOX5AP, C1orf29, SELL,STC1, LRMP, MYB, PTPN7, CXorf9, RHOH, ZNFN1A1, CENTB1, ADD2, CD1D, BATF,MAP4K1, CCR7, PDE4C, CD3G, CCR9, SP110, TNFAIP8, NAP1L1, CXCR4, ARHGEF6,GATA3, SELPLG, SEC31L2, CD3Z, SH2D1A, GZMB, CD1A, SCN3A, LAIR1, AF1Q,TRB@, DOCK2, MLC1, CD3D, T3JAM, CD6, ZAP70, IFI44, GPR65, PRF1, AIF1,WDR45, CD1E, CYFIP2, TARP, TRIM, ARHGAP15, NOTCH1, STAG3, NARF, TM6SF1,UBASH3A, and MGC5566, or wherein the method further comprises measuringa level of expression of at least one gene selected from the groupconsisting of FLJ10534, PTPRC, TRIM22, C18orf1, TRIM41, LAT, CD1C,MYBBP1A, CD53, FARSLA, PPP2CA, COL5A2, LAPTM5, CD53, CORO1A, PTPRCAP,PTPRC, HEM1, GMFG, ITK, CD1B, GMFG, PTPRCAP, PTPRC, CD53, CORO1A, HEM1,TCF7, PTPRC, HCLS1, ATP2A3, MYBL1, and FARSLA, or wherein the methodfurther comprises measuring a level of expression of at least onemicroRNA selected from the group consisting of hsa-mir-124a-3-prec,Hcd768, HUMTRF, hsa-mir-2,3-prec, hsa-mir-181b-prec, Hcd783,hsa-mir-2,2-prec, hsa-mir-124a-1-prec1, hsa-mir-342, hsa-mir-142-prec,HSHELA01, hsa-mir-223-prec, and Hcd754, wherein said level of expressionof said gene or microRNA indicates that said cell is sensitive toTeniposide.
 54. The method of claim 1, wherein said at least one gene isselected from the group consisting of ALDOC, C1QR1, SLA, WBSCR20A, MFNG,SELL, MYB, RHOH, ZNFN1A1, LCP2, MAP4K1, CBFA2T3, LCP1, SELPLG, CD3Z,LAIR1, WBSCR20C, CD3D, GPR65, ARHGAP15, FLJ10178, NARF, and PUS3, orwherein the method further comprises measuring a level of expression ofat least one gene selected from the group consisting of PTPRC, MYBBP1A,ICAM3, CD53, FARSLA, CD53, PTPRCAP, PTPRC, HEM1, GMFG, GMFG, PTPRCAP,PTPRC, CD53, HEM1, PTPRC, HCLS1, PRKCB1, PRKCB1, MYBL1, and FARSLA, orwherein the method further comprises measuring a level of expression ofat least one microRNA selected from the group consisting ofhsa-mir-025-prec, hsa-mir-007-1-prec, hsa-mir-093-prec-7.1=093-1,Hcd794, and hsa-mir-142-prec, wherein said level of expression of saidgene or microRNA indicates that said cell is sensitive to Dactinomycin.55. The method of claim 1, wherein said at least one gene is selectedfrom the group consisting of PPIB, ZFP36L2, IFI30, USP7, SRM, SH3BP5,ALDOC, FADS2, GUSB, PSCD1, IQGAP2, STS, MFNG, FLI1, PIM2, INPP4A, LRMP,ICAM2, EVI2A, MAL, BTN3A3, PTPN7, IL10RA, SPI1, TRAF1, ITGB7, ARHGAP6,MAP4K1, CD28, PTP4A3, LTB, C1orf38, WBSCR22, CD8B1, LCP1, FLJ13052,MEF2C, PSCDBP, IL16, SELPLG, MAGEA9, LAIR1, TNFRSF25, EVI2B, IGJ, PDCD4,RASA4, HA-1, PLCL2, RNASE6, WBSCR20C, NUP210, RPL10L, C11orf2, CABC1,ARHGEF3, TAPBPL, CHST12, FKBP11, FLJ35036, MYLIP, TXNDC5, PACAP, TOSO,PNAS-4, IL21R, and TCF4, or wherein the method further comprisesmeasuring a level of expression of at least one gene selected from thegroup consisting of CLTB, BTN3A2, BCL2, SETBP1, ICAM3, BCL2, BCL2, BCL2,CD53, CCND2, CLTB, CLTB, BCL2L11, BTN3A2, CD37, MYCL2, CTSS, LAPTM5,CD53, CORO1A, HEM1, CD53, CORO1A, HEM1, HCLS1, BCL2L11, MYCL1, MYC, andMAN1A1, or wherein the method further comprises measuring a level ofexpression of at least one microRNA selected from the group consistingof Hcd257, hsa-mir-148-prec, Hcd512, HPR227, Hcd421, MPR203,hsa-mir-0,7-prec, hsa-mir-219-2, hsa-mir-328, Hcd783, Hcd181, HPR213,hsa-mir-191-prec, hsa-mir-375, hsa-mir-2,2-prec, Hcd913, Hcd716, MPR207,HPR206, hsa-mir-016b-chr3, Hcd654, hsa-mir-195-prec, Hcd425,hsa-mir-148a, hsa-mir-142-prec, and hsa-mir-016a-chr13, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to Tretinoin.
 56. The method of claim 1, wherein said at leastone gene is selected from the group consisting of PDGFRB, KDR, KIT, andFLT3, or wherein the method further comprises measuring a level ofexpression of at least one gene selected from the group consisting ofFLT1, FLT4, PDGFRA, and CSF1R, wherein said level of expression of saidgene indicates that said cell is sensitive to sunitinib.
 57. The methodof claim 1, wherein said at least one gene is BCL2, wherein said levelof expression of said gene indicates that said cell is sensitive toSPC2996.
 58. The method of claim 1, wherein said at least one gene isselected from the group consisting of ARHGDIB, ZFP36L2, ITM2A, LGALS9,INPP5D, SATB1, TFDP2, IL2RG, CD48, SELL, ADA, LRMP, RIMS3, LCK, CXorf9,RHOH, ZNFN1A1, LCP2, CD1D, CD2, ZNF91, MAP4K1, CCR7, IGLL1, CD3G,ZNF430, CCR9, CXCR4, KIAA0922, TARP, FYN, SH2D1A, CD1A, LST1, LAIR1,TRB@, SEPT6, CD3D, CD6, AIF1, CD1E, TRIM, GLTSCR2, ARHGAP15, BIN2,SH3TC1, CECR1, BCL11B, GIMAP6, STAG3, GALNT6, MGC5566, PACAP, and LEF1,or wherein the method further comprises measuring a level of expressionof at least one gene selected from the group consisting of CD27BP,TRIM22, TRA@, C18orf1, EVL, PRKCH, TRIM41, PSCD2L, CD1C, ADAM11, ABCD2,CD24, CD29, CD37, GNA15, LAPTM5, CORO1A, HEM1, GMFG, GNA15, CD1B, GMFG,CORO1A, HEM1, GNA15, ITGB2, PRKCB1, ATP2A3, and PRKCB1, or wherein themethod further comprises measuring a level of expression of at least onemicroRNA selected from the group consisting of hsa-mir-092-prec-X=092-2,hsa-mir-181b-2, Hcd417, Hcd440_HPR257, hsa-mir-019b-2-prec,hsa-mir-2,3-prec, hsa-mir-033-prec, hsa-mir-092-prec-13=092-1,hsa-mir-181b-prec, hsa-mir-128b-prec, hsa-mir-526a-2, MPR95, HPR220,hsa-mir-133a-1, hsa-mir-148a, hsa-mir-142-prec, HPR169,hsa-mir-223-prec, hsa-mir-018-prec, hsa-mir-020-prec, and hsa-mir-484,wherein said level of expression of said gene or microRNA indicates thatsaid cell is sensitive to Ifosfamide.
 59. The method of claim 1, whereinsaid at least one gene is selected from the group consisting of MLP,GLUL, SLC9A3R1, ZFP36L2, INSIG1, TBL1X, NDUFAB1, EBP, TRIM14, SRPK2,PMM2, CLDN3, GCH1, ID11, TTF1, MYB, RASGRP1, HIST1H3H, CBFA2T3, SRRM2,ANAPC5, MBD4, GATA3, H1ST1H2BG, RAB14, PIK3R1, MGC50853, ELF1, ZRF1,ZNF394, S100A14, SLC6A14, GALNT6, SPDEF, TPRT, and CALML4, or whereinthe method further comprises measuring a level of expression of at leastone gene selected from the group consisting of EIF4A1, TFF1, TFF1,MYBBP1A, AKAP1, DGKZ, EIF4A1, KIAA0182, SLC19A1, ATP2A3, MYBL1,EIF4EBP2, G1P2, and MAN1A1, or wherein the method further comprisesmeasuring a level of expression of at least one microRNA selected fromthe group consisting of hsa-mir-092-prec-X=092-2, Hcd547, Hcd257,hsa-mir-148-prec, HUMTRS, hsa-mir-033-prec, hsa-mir-092-prec-13=092-1,hsa-mir-375, hsa-mir-095-prec-4, hsa-mir-025-prec, hsa-mir-202-prec,hsa-mir-007-1-prec, hsa-mir-093-prec-7.1=093-1, hsa-mir-106-prec-X,hsa-mir-142-prec, hsa-mir-223-prec, and hsa-mir-018-prec, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to Tamoxifen.
 60. The method of claim 1, wherein said at leastone gene is selected from the group consisting of CSDA, F8A1, KYNU,PHF14, SERPINB2, OPHN1, HRMT1L2, TNFRSF1A, PPP4C, CES1, TP53AP1, TM4SF4,RPL5, BC008967, TLK2, COL4A6, PAK3, RECK, LOC51321, MST4, DERP6, SCD4,and FLJ22800, or wherein the method further comprises measuring a levelof expression of at least one gene selected from the group consisting ofSTC2, BAX, CDKN1A, DDB2, RGS2, BAX, BAX, RPL13, RPL13, CDKN1A, andGABPB2, or wherein the method further comprises measuring a level ofexpression of at least one microRNA selected from the group consistingof HUMTRF, HUMTRN, hsa-mir-124a-1-prec1, hsa-mir-150-prec, Hcd923,HPR181, Hcd569, hsa-mir-199a-2-prec, Hcd754, and hsa-mir-4323p, whereinsaid level of expression of said gene or microRNA indicates that saidcell is sensitive to Floxuridine.
 61. The method of claim 1, whereinsaid at least one gene is selected from the group consisting of CSDA,UBE2L6, TAP1, RPS19, SERPINA1, C1QR1, SLA, GPSM3, PSMB9, EDG1, FMNL1,PTPN7, ZNFN1A1, CENTB1, BATF, MAP4K1, PDE4C, SP110, HLA-DRA, IFI16,HLA-DRB1, ARHGEF6, SELPLG, SEC31L2, CD3Z, PRKCQ, SH2D1A, GZMB, TRB@,HLA-DPA1, AIM1, DOCK2, CD3D, IFITM1, ZAP70, PRF1, C1orf24, ARHGAP15,C13orf18, and TM6SF1, or wherein the method further comprises measuringa level of expression of at least one gene selected from the groupconsisting of PTPRC, TRIM22, PSME2, LAT, METAP1, CD53, FARSLA, RPL13,RAC2, RPL13, PTMA, CD53, CORO1A, PTPRCAP, PTPRC, GMFG, ITK, GMFG,PTPRCAP, PTPRC, CD53, CORO1A, ITGB2, PTPRC, HCLS1, and FARSLA, orwherein the method further comprises measuring a level of expression ofat least one microRNA selected from the group consisting of HUMTRF,hsa-mir-380-5p, hsa-mir-342, hsa-mir-142-prec, and Hcd200, wherein saidlevel of expression of said gene or microRNA indicates that said cell issensitive to Irinotecan.
 62. The method of claim 1, wherein said atleast one gene is selected from the group consisting of STAT1, HSBP1,IFI30, RIOK3, TNFSF10, ALOX5AP, ADFP, IRS2, EFEMP2, RIPK2,DKFZp56411922, MT1K, RNASET2, EFHD2, TRIB3, ACSL5, IFIH1, and DNAPTP6,or wherein the method further comprises measuring a level of expressionof at least one gene selected from the group consisting of IFI27, OPTN,C20orf18, FN1, LOC51123, FN1, OPTN, and OPTN, or wherein the methodfurther comprises measuring a level of expression of at least onemicroRNA selected from the group consisting of Hcd289, Hcd939, Hcd330,HPR76, Hcd111, Hcd976, hsa-mir-15a, hsa-mir-001b-1-prec1, hsa-mir-450-1,hsa-mir-200b, Hcd578, and hsa-mir-200a-prec, wherein said level ofexpression of said gene or microRNA indicates that said cell issensitive to Satraplatin.
 63. The method of claim 1, wherein said levelof expression of said gene is determined by detecting the level of mRNAtranscribed from said gene.
 64. The method of claim 1, wherein saidlevel of expression of said gene is determined by detecting the level ofa protein product of said gene.
 65. The method of claim 1, wherein saidlevel of expression of said gene is determined by detecting the level ofthe biological activity of a protein product of said gene.
 66. Themethod of claim 1, wherein an increase in the level of expression ofsaid gene or microRNA indicates increased sensitivity of said cell tosaid treatment.
 67. The method of claim 1, wherein said cell is a cancercell.
 68. The method of claim 1, wherein a decrease in the level ofexpression of said gene or microRNA indicates increased sensitivity ofsaid cell to said treatment.
 69. The method of claim 1, wherein saidlevel of expression of said gene or microRNA is measured using aquantitative reverse transcription-polymerase chain reaction (qRT-PCR).70. A method for determining the development of resistance of a cell ina patient to a treatment to which said cell in said patient haspreviously been sensitive, said method comprising measuring a level ofexpression of at least one gene or microRNA of claim 1 of said cell,wherein a decrease in said level of expression of said gene or microRNAin said cell relative to the level of expression of said gene ormicroRNA in a control cell sensitive to said treatment indicatesresistance or a propensity to develop resistance to the treatment bysaid patient.
 71. A method for determining the development of resistanceof a cell in a patient to a treatment to which said cell in said patienthas previously been sensitive, said method comprising measuring a levelof expression of at least one gene or microRNA of claim 1 in said cell,wherein an increase in said level of expression of said gene or microRNAin said cell relative to the level of expression of said gene ormicroRNA in a control cell sensitive to said treatment indicatesresistance or a propensity to develop resistance to the treatment bysaid patient.
 72. A method of determining sensitivity of a cancerpatient to a treatment for cancer comprising measuring a level ofexpression of at least one microRNA in a cell of said patient, saidmicroRNA selected from the group consisting of ath-MIR180aNo2, Hcd102left, Hcd111 left, Hcd115 left, Hcd120 left, Hcd142 right, Hcd145 left,Hcd148_HPR225 left, Hcd181 left, Hcd181 right, Hcd210_HPR205 right,Hcd213_HPR182 left, Hcd230 left, Hcd243 right, Hcd246 right, Hcd248right, Hcd249 right, Hcd250 left, Hcd255 left, Hcd257 left, Hcd257right, Hcd263 left, Hcd266 left, Hcd270 right, Hcd279 left, Hcd279right, Hcd28_HPR39left, Hcd28_HPR39right, Hcd282PO right, Hcd289 left,Hcd294 left, Hcd318 right, Hcd323 left, Hcd330 right, Hcd338 left,Hcd340 left, Hcd350 right, Hcd355_HPR190 left, Hcd361 right, Hcd366left, Hcd373 right, Hcd383 left, Hcd383 right, Hcd384 left, Hcd397 left,Hcd404 left, Hcd412 left, Hcd413 right, Hcd415 right, Hcd417 right,Hcd421 right, Hcd425 left, Hcd438right, Hcd434 right, Hcd438 left,Hcd440_HPR257 right, Hcd444 right, Hcd447 right, Hcd448 left, Hcd498right, Hcd503 left, Hcd511 right, Hcd512 left, Hcd514 right, Hcd517left, Hcd517 right, Hcd530 right, Hcd536_HPR104 right, Hcd542 left,Hcd544 left, Hcd547 left, Hcd559 right, Hcd562 right, Hcd569 right,Hcd570 right, Hcd578 right, Hcd581 right, Hcd586 left, Hcd586 right,Hcd587 right, Hcd605 left, Hcd605 left, Hcd605 right, Hcd608 right,Hcd627 left, Hcd631 left, Hcd631 right, Hcd634 left, Hcd642 right,Hcd649 right, Hcd654 left, Hcd658 right, Hcd669 right, Hcd674 left,Hcd678 right, Hcd683 left, Hcd684 right, Hcd689 right, Hcd690 right,Hcd691 right, Hcd693 right, Hcd697 right, Hcd704 left, Hcd704 left,Hcd712 right, Hcd716 right, Hcd731 left, Hcd738 left, Hcd739 right,Hcd739 right, Hcd749 right, Hcd753 left, Hcd754 left, Hcd755 left,Hcd760 left, Hcd763 right, Hcd768 left, Hcd768 right, Hcd770 left,Hcd773 left, Hcd777 left, Hcd778 right, Hcd781 left, Hcd781 right,Hcd782 left, Hcd783 left, Hcd788 left, Hcd794 right, Hcd796 left, Hcd799left, Hcd807 right, Hcd812 left, Hcd817 left, Hcd817 right, Hcd829right, Hcd852 right, Hcd861 right, Hcd863PO right, Hcd866 right, Hcd869left, Hcd873 left, Hcd886 right, Hcd889 right, Hcd891 right, Hcd892left, Hcd913 right, Hcd923 left, Hcd923 right, Hcd938 left, Hcd938right, Hcd939 right, Hcd946 left, Hcd948 right, Hcd960 left, Hcd965left, Hcd970 left, Hcd975 left, Hcd976 right, Hcd99 right, HPR100 right,HPR129 left, HPR154 left, HPR159 left, HPR163 left, HPR169 right, HPR172right, HPR181 left, HPR187 left, HPR199 right, HPR206 left, HPR213right, HPR214 right, HPR220 left, HPR220 right, HPR227 right, HPR232right, HPR233 right, HPR244 right, HPR262 left, HPR264 right, HPR266right, HPR271 right, HPR76 right, hsa_mir_(—)490_Hcd20 right, HSHELA01,HSTRNL, HUMTRAB, HUMTRF, HUMTRN, HUMTRS, HUMTRV1A, let-7f-2-prec2,mir-001b-1-prec1, mir-001b-2-prec, mir-007-1-prec, mir-007-2-precNo2,mir-010a-precNo1, mir-015b-precNo2, mir-016a-chr13, mir-016b-chr3,mir-017-precNo1, mir-017-precNo2, mir-018-prec, mir-019a-prec,mir-019b-1-prec, mir-019b-2-prec, mir-020-prec, mir-022-prec,mir-023a-prec, mir-023b-prec, mir-024-2-prec, mir-025-prec,mir-027b-prec, mir-029c-prec, mir-032-precNo2, mir-033b-prec,mir-033-prec, mir-034-precNo1, mir-034-precNo2,mir-092-prec-13=092-1No2, mir-092-prec-X=092-2, mir-093-prec-7.1=093-1,mir-095-prec-4, mir-096-prec-7No1,mir-096-prec-7No2, mir-098-prec-X,mir-099b-prec-19No1, mir-100-1/2-prec, mir-100No1, mir-101-prec-9,mir-102-prec-1, mir-103-2-prec, mir-103-prec-5=103-1, mir-106aNo1,mir-106-prec-X, mir-107No1, mir-107-prec-10, mir-122a-prec,mir-123-precNo1, mir-123-precNo2, mir-124a-1-prec1, mir-124a-2-prec,mir-124a-3-prec, mir-125b-1, mir-125b-2-precNo2, mir-127-prec,mir-128b-precNo1, mir-128b-precNo2, mir-133a-1, mir-135-2-prec,mir-136-precNo2, mir-138-1-prec, mir-140No2, mir-142-prec, mir-143-prec,mir-144-precNo2, mir-145-prec, mir-146bNo1, mir-146-prec, mir-147-prec,mir-148aNo1, mir-148-prec, mir-149-prec, mir-150-prec, mir-153-1-prec1,mir-154-prec1No1, mir-155-prec, mir-15aNo1, mir-16-1No1, mir-16-2No1,mir-181a-precNo1, mir-181b-1No1, mir-181b-2No1, mir-181b-precNo1,mir-181b-precNo2, mir-181c-precNo1, mir-181dNo1, mir-188-prec,mir-18bNo2, mir-191-prec, mir-192No2, mir-193bNo2, mir-194-2No1,mir-195-prec, mir-196-2-precNo2, mir-197-prec, mir-198-prec,mir-199a-1-prec, mir-199a-2-prec, mir-199b-precNo1, mir-200a-prec,mir-200bNo1, mir-200bNo2, mir-202*, mir-202-prec, mir-204-precNo2,mir-205-prec, mir-208-prec, mir-20bNo1, mir-2,2-precNo1,mir-2,2-precNo2, mir-2,3-precNo1, mir-2,4-prec, mir-2,5-precNo2,mir-2,6-precNo1, mir-219-2No1, mir-2,9-prec, mir-223-prec, mir-29b-1No1,mir-29b-2=102prec7.1=7.2, mir-321No1, mir-321No2, mir-324No1,mir-324No2, mir-328No1, mir-342No1, mir-361No1, mir-367No1, mir-370No1,mir-371No1, miR-373*No1, mir-375, mir-376aNo1, mir-379No1, mir-380-5p,mir-382, mir-384, mir-409-3p, mir-423No1, mir-424No2, mir-429No1,mir-429No2, mir-4323p, mir-4325p, mir-449No1, mir-450-1, mir-450-2No1,mir-483No1, mir-484, mir-487No1, mir-495No1, mir-499No2, mir-501No2,mir-503No1, mir-509No1, mir-514-1No2, mir-515-15p, mir-515-23p,mir-516-33p, mir-516-43p, mir-518e/526c, mir-519a-1/52, mir-519a-2No2,mir-519b, mir-519c/52, mir-520c/52, mir-526a-2No1, mir-526a-2No2, MPR103right, MPR121 left, MPR121 left, MPR130 left, MPR130 right, MPR133right, MPR141 left, MPR151 left, MPR156 left, MPR162 left, MPR174 left,MPR174 right, MPR185 right, MPR197 right, MPR203 left, MPR207 right,MPR215 left, MPR216 left, MPR224 left, MPR224 right, MPR228 left, MPR234right, MPR237 left, MPR243 left, MPR244 right, MPR249 left, MPR254right, MPR74 left, MPR88 right, and MPR95 left, wherein said level ofexpression of said microRNA indicates said cell is sensitive to saidtreatment. 73-136. (canceled)
 137. A kit comprising a single-strandednucleic acid molecule that is substantially complementary to orsubstantially identical to at least 5 consecutive nucleotides of atleast one gene selected from the group consisting of ACTB, ACTN4, ADA,ADAM9, ADAMTS1, ADD1, AF1Q, AIF1, AKAP1, AKAP13, AKR1C1, AKT1, ALDH2,ALDOC, ALG5, ALMS1, ALOX15B, AMIGO2, AMPD2, AMPD3, ANAPC5, ANP32A,ANP32B, ANXA1, AP1G2, APOBEC3B, APRT, ARHE, ARHGAP15, ARHGAP25, ARHGDIB,ARHGEF6, ARL7, ASAH1, ASPH, ATF3, ATIC, ATP2A2, ATP2A3, ATP5D, ATP5G2,ATP6V1B2, BC008967, BCAT1, BCHE, BCL11B, BDNF, BHLHB2, BIN2, BLMH, BMI1,BNIP3, BRDT, BRRN1, BTN3A3, C11orf2, C14orf139, C15orf25, C18orf10,C1orf24, C1orf29, C1orf38, C1QR1, C22orf18, C6orf32, CACNA1G, CACNB3,CALM1, CALML4, CALU, CAP350, CASP2, CASP6, CASP7, CAST, CBLB, CCNA2,CCNB1IP1, CCND3, CCR7, CCR9, CD1A, CD1C, CD1D, CD1E, CD2, CD28, CD3D,CD3E, CD3G, CD3Z, CD44, CD47, CD59, CD6, CD63, CD8A, CD8B1, CD99, CDC10,CDCl₄B, CDH11, CDH2, CDKL5, CDKN2A, CDW52, CECR1, CENPB, CENTB1, CENTG2,CEP1, CG018, CHRNA3, CHS1, CIAPIN1, CKAP4, CKIP-1, CNP, COL4A1, COL5A2,COL6A1, CORO1C, CRABP1, CRK, CRY1, CSDA, CTBP1, CTSC, CTSL, CUGBP2,CUTC, CXCL1, CXCR4, CXorf9, CYFIP2, CYLD, CYR61, DATF1, DAZAP1, DBN1,DBT, DCTN1, DDX18, DDX5, DGKA, DIAPH1, DKC1, DKFZP434J154, DKFZP564C186,DKFZP564G2022, DKFZp564J157, DKFZP564K0822, DNAJC10, DNAJC7, DNAPTP6,DOCK10, DOCK2, DPAGT1, DPEP2, DPYSL3, DSIPI, DUSP1, DXS9879E, EEF1B2,EFNB2, EHD2, EIF5A, ELK3, ENO2, EPAS1, EPB41L4B, ERCC2, ERG, ERP70,EVER1, EVI2A, EVL, EXT1, EZH2, F2R, FABP5, FAD104, FAM46A, FAU, FCGR2A,FCGR2C, FER1L3, FHL1, FHOD1, FKBP1A, FKBP9, FLJ10350, FLJ10539,FLJ10774, FLJ12270, FLJ13373, FLJ20859, FLJ21159, FLJ22457, FLJ35036,FLJ46603, FLNC, FLOT1, FMNL1, FNBP1, FOLH1, FOXF2, FSCN1, FTL, FYB, FYN,GOS2, G6PD, GALIG, GALNT6, GATA2, GATA3, GFPT1, GIMAP5, GIT2, GJA1,GLRB, GLTSCR2, GLUL, GMDS, GNAQ, GNB2, GNB5, GOT2, GPR65, GPRASP1,GPSM3, GRP58, GSTM2, GTF3A, GTSE1, GZMA, GZMB, H1F0, H1FX, H2AFX, H3F3A,HA-1, HEXB, HIC, HIST1H4C, HK1, HLA-A, HLA-B, HLA-DRA, HMGA1, HMGN2,HMMR, HNRPA1, HNRPD, HNRPM, HOXA9, HRMT1L1, HSA9761, HSPA5, HSU79274,HTATSF1, ICAM1, ICAM2, IER3, IFI16, IFI44, IFITM2, IFITM3, IFRG28,IGFBP2, IGSF4, IL13RA2, IL21R, IL2RG, IL4R, IL6, IL6R, IL6ST, IL8,IMPDH2, INPP5D, INSIG1, IQGAP1, IQGAP2, IRS2, ITGA5, ITM2A, JARID2,JUNB, K-ALPHA-1, KHDRBS1, KIAA0355, KIAA0802, KIAA0877, KIAA0922,KIAA1078, KIAA1128, KIAA1393, KIFC1, LAIR1, LAMB1, LAMB3, LAT, LBR, LCK,LCP1, LCP2, LEF1, LEPRE1, LGALS1, LGALS9, LHFPL2, LNK, LOC54103,LOC55831, LOC81558, LOC94105, LONP, LOX, LOXL2, LPHN2, LPXN, LRMP,LRP12, LRRC5, LRRN3, LST1, LTB, LUM, LY9, LY96, MAGEB2, MAL, MAP1B,MAP1LC3B, MAP4K1, MAPK1, MARCKS, MAZ, MCAM, MCL1, MCM5, MCM7, MDH2,MDN1, MEF2C, MFNG, MGC17330, MGC21654, MGC2744, MGC4083, MGC8721,MGC8902, MGLL, MLPH, MPHOSPH6, MPP1, MPZL1, MRP63, MRPS2, MT1E, MT1K,MUF1, MVP, MYB, MYL9, MYO1B, NAP1L1, NAP1L2, NARF, NASP, NCOR2, NDN,NDUFAB1, NDUFS6, NFKBIA, NID2, NIPA2, NME4, NME7, NNMT, NOL5A, NOL8,NOMO2, NOTCH1, NPC1, NQO1, NR1D2, NUDC, NUP210, NUP88, NVL, NXF1, OBFC1,OCRL, OGT, OXA1L, P2RX5, P4HA1, PACAP, PAF53, PAFAH1B3, PALM2-AKAP2,PAX6, PCBP2, PCCB, PFDN5, PFN1, PFN2, PGAM1, PHEMX, PHLDA1, PIM2,PITPNC1, PLAC8, PLAGL1, PLAUR, PLCB1, PLEK2, PLEKHC1, PLOD2, PLSCR1,PNAS-4, PNMA2, POLR2F, PPAP2B, PRF1, PRG1, PRIM1, PRKCH, PRKCQ, PRKD2,PRNP, PRP19, PRPF8, PRSS23, PSCDBP, PSMB9, PSMC3, PSME2, PTGER4, PTGES2,PTOV1, PTP4A3, PTPN7, PTPNS1, PTRF, PURA, PWP1, PYGL, QKI, RAB3GAP,RAB7L1, RAB9P40, RAC2, RAFTLIN, RAG2, RAP1B, RASGRP2, RBPMS, RCN1, RFC3,RFC5, RGC32, RGS3, RHOH, RIMS3, RIOK3, RIPK2, RIS1, RNASE6, RNF144,RPL10, RPL10A, RPL12, RPL13A, RPL17, RPL18, RPL36A, RPLP0, RPLP2, RPS15,RPS19, RPS2, RPS4X, RPS4Y1, RRAS, RRAS2, RRBP1, RRM2, RUNX1, RUNX3,S100A4, SART3, SATB1, SCAP1, SCARB1, SCN3A, SEC31L2, SEC61G, SELL,SELPLG, SEMA4G, SEPT10, SEPT6, SERPINA1, SERPINB1, SERPINB6, SFRS5,SFRS6, SFRS7, SH2D1A, SH3GL3, SH3TC1, SHD1, SHMT2, SIAT1, SKB1, SKP2,SLA, SLC1A4, SLC20A1, SLC25A15, SLC25A5, SLC39A14, SLC39A6, SLC43A3,SLC4A2, SLC7A11, SLC7A6, SMAD3, SMOX, SNRPA, SNRPB, SOD2, SOX4, SP140,SPANXC, SPI1, SRF, SRM, SSA2, SSBP2, SSRP1, SSSCA1, STAG3, STAT1, STAT4,STAT5A, STC1, STC2, STOML2, T3JAM, TACC1, TACC3, TAF5, TAL1, TAP1, TARP,TBCA, TCF12, TCF4, TFDP2, TFPI, TIMM17A, TIMP1, TJP1, TK2, TM4SF1,TM4SF2, TM4SF8, TM6SF1, TMEM2, TMEM22, TMSB10, TMSNB, TNFAIP3, TNFAIP8,TNFRSF10B, TNFRSF1A, TNFRSF7, TNIK, TNPO1, TOB1, TOMM20, TOX, TPK1,TPM2, TRA@, TRA1, TRAM2, TRB@, TRD@, TRIM, TRIM14, TRIM22, TRIM28,TRIP13, TRPV2, TUBGCP3, TUSC3, TXN, TXNDC5, UBASH3A, UBE2A, UBE2L6,UBE2S, UCHL1, UCK2, UCP2, UFD1L, UGDH, ULK2, UMPS, UNG, USP34, USP4,VASP, VAV1, VLDLR, VWF, WASPIP, WBSCR20A, WBSCR20C, WHSC1, WNT5A, ZAP70,ZFP36L1, ZNF32, ZNF335, ZNF593, ZNFN1A1, and ZYX, wherein saidsingle-stranded nucleic acid molecule allows detection of a level ofexpression of said gene when said single-stranded nucleic acid moleculeis contacted with a nucleic acid molecule expressed from said gene, orits complement, under conditions allowing hybridization to occur betweensaid single-stranded nucleic acid molecule and said nucleic acidmolecule expressed from said gene, said kit further comprisinginstructions for applying nucleic acids collected from a sample from acancer patient, instructions for measuring the level of expression ofsaid gene, and instructions for determining said cell's sensitivity to atreatment for cancer. 138-204. (canceled)
 205. A kit comprising asingle-stranded nucleic acid molecule that is substantiallycomplementary to or substantially identical to at least 5 consecutivenucleotides of at least one microRNA selected from the group consistingof ath-MIR180aNo2, Hcd102 left, Hcd111 left, Hcd115 left, Hcd120 left,Hcd142 right, Hcd145 left, Hcd148_HPR225 left, Hcd181 left, Hcd181right, Hcd210_HPR205 right, Hcd213_HPR182 left, Hcd230 left, Hcd243right, Hcd246 right, Hcd248 right, Hcd249 right, Hcd250 left, Hcd255left, Hcd257 left, Hcd257 right, Hcd263 left, Hcd266 left, Hcd270 right,Hcd279 left, Hcd279 right, Hcd28_HPR39left, Hcd28_HPR39right, Hcd282POright, Hcd289 left, Hcd294 left, Hcd318 right, Hcd323 left, Hcd330right, Hcd338 left, Hcd340 left, Hcd350 right, Hcd355_HPR190 left,Hcd361 right, Hcd366 left, Hcd373 right, Hcd383 left, Hcd383 right,Hcd384 left, Hcd397 left, Hcd404 left, Hcd412 left, Hcd413 right, Hcd415right, Hcd417 right, Hcd421 right, Hcd425 left, Hcd438right, Hcd434right, Hcd438 left, Hcd440_HPR257 right, Hcd444 right, Hcd447 right,Hcd448 left, Hcd498 right, Hcd503 left, Hcd511 right, Hcd512 left,Hcd514 right, Hcd517 left, Hcd517 right, Hcd530 right, Hcd536_HPR104right, Hcd542 left, Hcd544 left, Hcd547 left, Hcd559 right, Hcd562right, Hcd569 right, Hcd570 right, Hcd578 right, Hcd581 right, Hcd586left, Hcd586 right, Hcd587 right, Hcd605 left, Hcd605 left, Hcd605right, Hcd608 right, Hcd627 left, Hcd631 left, Hcd631 right, Hcd634left, Hcd642 right, Hcd649 right, Hcd654 left, Hcd658 right, Hcd669right, Hcd674 left, Hcd678 right, Hcd683 left, Hcd684 right, Hcd689right, Hcd690 right, Hcd691 right, Hcd693 right, Hcd697 right, Hcd704left, Hcd704 left, Hcd712 right, Hcd716 right, Hcd731 left, Hcd738 left,Hcd739 right, Hcd739 right, Hcd749 right, Hcd753 left, Hcd754 left,Hcd755 left, Hcd760 left, Hcd763 right, Hcd768 left, Hcd768 right,Hcd770 left, Hcd773 left, Hcd777 left, Hcd778 right, Hcd781 left, Hcd781right, Hcd782 left, Hcd783 left, Hcd788 left, Hcd794 right, Hcd796 left,Hcd799 left, Hcd807 right, Hcd812 left, Hcd817 left, Hcd817 right,Hcd829 right, Hcd852 right, Hcd861 right, Hcd863PO right, Hcd866 right,Hcd869 left, Hcd873 left, Hcd886 right, Hcd889 right, Hcd891 right,Hcd892 left, Hcd913 right, Hcd923 left, Hcd923 right, Hcd938 left,Hcd938 right, Hcd939 right, Hcd946 left, Hcd948 right, Hcd960 left,Hcd965 left, Hcd970 left, Hcd975 left, Hcd976 right, Hcd99 right, HPR100right, HPR129 left, HPR154 left, HPR159 left, HPR163 left, HPR169 right,HPR172 right, HPR181 left, HPR187 left, HPR199 right, HPR206 left,HPR213 right, HPR214 right, HPR220 left, HPR220 right, HPR227 right,HPR232 right, HPR233 right, HPR244 right, HPR262 left, HPR264 right,HPR266 right, HPR271 right, HPR76 right, hsa_mir_(—)490_Hcd20 right,HSHELA01, HSTRNL, HUMTRAB, HUMTRF, HUMTRN, HUMTRS, HUMTRV1A,let-7f-2-prec2, mir-001b-1-prec1, mir-001b-2-prec, mir-007-1-prec,mir-007-2-precNo2, mir-010a-precNo1, mir-015b-precNo2, mir-016a-chr13,mir-016b-chr3, mir-017-precNo1, mir-017-precNo2, mir-018-prec,mir-019a-prec, mir-019b-1-prec, mir-019b-2-prec, mir-020-prec,mir-022-prec, mir-023a-prec, mir-023b-prec, mir-024-2-prec,mir-025-prec, mir-027b-prec, mir-029c-prec, mir-032-precNo2,mir-033b-prec, mir-033-prec, mir-034-precNo1, mir-034-precNo2,mir-092-prec-13=092-1No2, mir-092-prec-X=092-2, mir-093-prec-7.1=093-1,mir-095-prec-4, mir-096-prec-7No1, mir-096-prec-7No2, mir-098-prec-X,mir-099b-prec-19No1, mir-100-1/2-prec, mir-100No1, mir-101-prec-9,mir-102-prec-1, mir-103-2-prec, mir-103-prec-5=103-1, mir-106aNo1,mir-106-prec-X, mir-107No1, mir-107-prec-10, mir-122a-prec,mir-123-precNo1, mir-123-precNo2, mir-124a-1-prec1, mir-124a-2-prec,mir-124a-3-prec, mir-125b-1, mir-125b-2-precNo2, mir-127-prec,mir-128b-precNo1, mir-128b-precNo2, mir-133a-1, mir-135-2-prec,mir-136-precNo2, mir-138-1-prec, mir-140No2, mir-142-prec, mir-143-prec,mir-144-precNo2, mir-145-prec, mir-146bNo1, mir-146-prec, mir-147-prec,mir-148aNo1, mir-148-prec, mir-149-prec, mir-150-prec, mir-153-1-prec1,mir-154-prec1No1, mir-155-prec, mir-15aNo1, mir-16-1No1, mir-16-2No1,mir-181a-precNo1, mir-181b-1No1, mir-181b-2No1, mir-181b-precNo1,mir-181b-precNo2, mir-181c-precNo1, mir-181dNo1, mir-188-prec,mir-18bNo2, mir-191-prec, mir-192No2, mir-193bNo2, mir-194-2No1,mir-195-prec, mir-196-2-precNo2, mir-197-prec, mir-198-prec,mir-199a-1-prec, mir-199a-2-prec, mir-199b-precNo1, mir-200a-prec,mir-200bNo1, mir-200bNo2, mir-202*, mir-202-prec, mir-204-precNo2,mir-205-prec, mir-208-prec, mir-20bNo1, mir-2,2-precNo1,mir-2,2-precNo2, mir-2,3-precNo1, mir-2,4-prec, mir-2,5-precNo2,mir-2,6-precNo1, mir-219-2No1, mir-2,9-prec, mir-223-prec, mir-29b-1No1,mir-29b-2=102prec7.1=7.2, mir-321No1, mir-321No2, mir-324No1,mir-324No2, mir-328No1, mir-342No1, mir-361No1, mir-367No1, mir-370No1,mir-371No1, miR-373*No1, mir-375, mir-376aNo1, mir-379No1, mir-380-5p,mir-382, mir-384, mir-409-3p, mir-423No1, mir-424No2, mir-429No1,mir-429No2, mir-4323p, mir-4325p, mir-449No1, mir-450-1, mir-450-2No1,mir-483No1, mir-484, mir-487No1, mir-495No1, mir-499No2, mir-501No2,mir-503No1, mir-509No1, mir-514-1No2, mir-515-15p, mir-515-23p,mir-516-33p, mir-516-43p, mir-518e/526c, mir-519a-1/52, mir-519a-2No2,mir-519b, mir-519c/52, mir-520c/52, mir-526a-2No1, mir-526a-2No2, MPR103right, MPR121 left, MPR121 left, MPR130 left, MPR130 right, MPR133right, MPR141 left, MPR151 left, MPR156 left, MPR162 left, MPR174 left,MPR174 right, MPR185 right, MPR197 right, MPR203 left, MPR207 right,MPR215 left, MPR216 left, MPR224 left, MPR224 right, MPR228 left, MPR234right, MPR237 left, MPR243 left, MPR244 right, MPR249 left, MPR254right, MPR74 left, MPR88 right, and MPR95 left, wherein saidsingle-stranded nucleic acid molecule allows detection of a level ofexpression of said microRNA when said single-stranded nucleic acidmolecule is contacted with said microRNA, or its complement, underconditions allowing hybridization to occur between said single-strandednucleic acid molecule and said microRNA, said kit further comprisinginstructions for applying nucleic acids collected from a sample from acancer patient, instructions for measuring the level of expression ofsaid microRNA, and instructions for determining said cell's sensitivityto a treatment for cancer. 206-269. (canceled)
 270. A method ofidentifying biomarkers useful for the determination of sensitivity of acancer patient to a treatment for cancer comprising: a. obtainingpluralities of measurements of the level of expression of a gene ormicroRNA in different cell types and measurements of the growth of saidcell types in the presence of a treatment for cancer relative to thegrowth of said cell types in the absence of said treatment for cancer;b. correlating each plurality of measurements of the level of expressionof said gene or microRNA in said cells with the growth of said cells toobtain a correlation coefficient; c. selecting the median correlationcoefficient calculated for said gene or microRNA; and d. identifyingsaid gene or microRNA as a biomarker for use in determining thesensitivity of a cancer patient to said treatment for cancer if saidmedian correlation coefficient exceeds 0.3. 271-280. (canceled)
 281. Amethod of determining sensitivity of a cancer patient to a treatment forcancer comprising: a. obtaining a measurement of the level of expressionof a gene or microRNA in a sample from said cancer patient; b. applyinga model predictive of sensitivity to a treatment for cancer to saidmeasurement, wherein said model is developed using an algorithm selectedfrom the group consisting of linear sums, nearest neighbor, nearestcentroid, linear discriminant analysis, support vector machines, andneural networks; and c. predicting whether or not said cancer patientwill be responsive to said treatment for cancer. 282-301. (canceled)